Method and apparatus for performing communication in wireless communication system

Abstract

Provided are: a method for performing wireless communication; and an apparatus supporting same. The method may comprise the steps of: obtaining, by a first device, sensing resolution-related information; including, by the first device, the sensing resolution-related information in assistance information; and transmitting, by the first device, the assistance information including the sensing resolution-related information, to a second device.

Description

Method and apparatus for performing communication in a wireless communication system

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

[0002] 5G NR is a successor technology to LTE (long term evolution) and is a new clean-slate type mobile communication system with characteristics such as high performance, low latency, and high availability. 5G NR can utilize all available spectrum resources, ranging from low frequency bands below 1 GHz to mid-frequency bands from 1 GHz to 10 GHz, and high frequency (millimeter wave) bands above 24 GHz.

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

[0005] According to one embodiment of the present disclosure, a method may be provided. For example, the method may include: a first device acquiring information related to a sensing resolution; a first device including the information related to the sensing resolution in auxiliary information; and a first device transmitting the auxiliary information including the information related to the sensing resolution to a second device.

[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 connected to the at least one processor and storing instructions. For example, based on the instructions executed by the at least one processor, the first device may: acquire information related to a sensing resolution; include said information related to the sensing resolution in auxiliary information; and transmit said auxiliary information including said information related to the sensing resolution to a second device.

[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 connected to the at least one processor and storing instructions. For example, the instructions may cause the first device, based on execution by the at least one processor: to acquire information related to a sensing resolution; to include said information related to the sensing resolution in auxiliary information; and to transmit said auxiliary information including said information related to the sensing resolution to a second device.

[0008] According to one embodiment of the present disclosure, a non-transient computer-readable storage medium recording instructions may be provided. For example, when the instructions are executed, the first device may: acquire information related to a sensing resolution; include said information related to the sensing resolution in auxiliary information; and transmit said auxiliary information including said information related to the sensing resolution to a second device.

[0009] According to one embodiment of the present disclosure, a method may be provided. For example, the method may include the step of a second device establishing a radio resource control (RRC) connection with a first device; and the step of, based on the RRC connection, the second device receiving auxiliary information including information related to a sensing resolution from the first device.

[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 connected to the at least one processor and storing instructions. For example, the instructions may cause the second device to: establish a radio resource control (RRC) connection with the first device based on execution by the at least one processor; and receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection.

[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 connected to the at least one processor and storing instructions. For example, the instructions may cause the second device to: establish a radio resource control (RRC) connection with the first device based on execution by the at least one processor; and receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection.

[0012] According to one embodiment of the present disclosure, a non-transient computer-readable storage medium recording instructions may be provided. For example, when the instructions are executed, the second device may: establish a radio resource control (RRC) connection with the first device; and receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection.

[0013] FIG. 1 illustrates a communication procedure between devices according to one embodiment of the present disclosure.

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

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

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

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

[0018] FIG. 6 shows 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 an embodiment of the present disclosure.

[0020] FIG. 8 shows an example of a sensing operation according to one embodiment of the present disclosure.

[0021] FIG. 9 shows an example of six sensing scenarios for a sensing service according to one embodiment of the present disclosure.

[0022] FIG. 10 shows a QoS model for a communication service according to one embodiment of the present disclosure.

[0023] FIG. 11 shows a functional framework for AI / ML (Artificial Intelligence and Machine Learning) according to one embodiment of the present disclosure.

[0024] FIG. 12 shows an example of a reporting procedure according to one embodiment of the present disclosure.

[0025] FIG. 13 illustrates a procedure performed by a first device according to one embodiment of the present disclosure.

[0026] FIG. 14 illustrates a procedure performed by a second device according to one embodiment of the present disclosure.

[0027] FIG. 15 shows a communication system (1) according to one embodiment of the present disclosure.

[0028] FIG. 16 shows a wireless device according to one embodiment of the present disclosure.

[0029] FIG. 17 shows a signal processing circuit for a transmission signal according to one embodiment of the present disclosure.

[0030] FIG. 18 shows a wireless device according to one embodiment of the present disclosure.

[0031] FIG. 19 shows a portable device according to one embodiment of the present disclosure.

[0032] In the present disclosure, "A or B" may mean "only A," "only B," or "both A and B." Alternatively, in the present disclosure, "A or B" may be interpreted as "A and / or B." For example, in the present disclosure, "A, B or C" may mean "only A," "only B," "only C," or "any combination of A, B and C."

[0033] A slash ( / ) or a comma used in the present disclosure 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."

[0034] 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 as synonymous with "at least one of A and B."

[0035] Additionally, in the present disclosure, "at least one of A, B and C" may 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" may mean "at least one of A, B and C."

[0036] 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, the "control information" of 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."

[0037] In the following explanation, 'when, if, in case of' can be replaced with 'based on'.

[0038] Technical features described individually within one drawing in this disclosure may be implemented individually or simultaneously.

[0039] In the present disclosure, a higher layer parameter may be a parameter that is set for the terminal, pre-set, or pre-defined. For example, a base station or a network may transmit the higher layer parameter to the terminal. For example, the higher layer parameter may be transmitted via radio resource control (RRC) signaling or medium access control (MAC) signaling.

[0040] In the present disclosure, "configured or defined" may be interpreted as being configured or pre-configured to a device through pre-defined signaling from a base station or network (e.g., SIB, MAC, RRC, DCI (downlink control information), etc.). In the present disclosure, "configured or defined" may be interpreted as being configured or pre-configured to a device through pre-defined signaling from another device (e.g., MAC, RRC, SCI (sidelink control information), control information signaled between devices, etc.). In the present disclosure, "configured or defined" may be interpreted as being pre-configured to a device.

[0041] In the present disclosure, 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.

[0042] The technology proposed in this 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.

[0043] The technology proposed in this disclosure can be implemented as 6G wireless technology and can be applied to various 6G systems. For example, 6G systems may have key factors such as eMBB (enhanced mobile broadband), URLLC (ultra-reliable low latency communications), mMTC (massive machine-type communication), AI (artificial intelligence) integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0044] FIG. 1 illustrates a communication procedure between devices 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, suggestions, methods, and / or operations of the embodiments may be omitted.

[0045] Referring to FIG. 1, in step S101, the first device and the second device can perform synchronization. For example, the first device may be a terminal and / or at least one of the devices proposed in the present disclosure. For example, the second device may 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 may perform an initial cell search operation. For example, the first device may detect at least one synchronization signal transmitted according to a rule predefined by the second device. Here, for example, the synchronization signal may include a plurality of synchronization signals (e.g., primary synchronization signal, secondary synchronization signal, etc.) classified according to structure or use. 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., cell identifier).

[0046] In step S103, the first device may obtain system information transmitted by the second device. For example, the system information may include information related to the attributes, characteristics, and / or capabilities of the second device that are necessary 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 the system information prior to receiving the system information. For example, the request and provision of the system information may be performed after a random access procedure described later.

[0047] In step S105, the first device and the second device may perform a random access procedure. For example, the first device may transmit and / or receive at least one message for the random access procedure (e.g., random access preamble, random access response message, etc.) based on information related to the 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 may transmit a preamble (e.g., Msg1) through the random access channel, and the first device may receive a random access response message (e.g., Msg2). The first device may transmit a message (e.g., Msg3) containing 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 may receive a message (e.g., Msg4) for contention resolution and / or connection establishment. For example, Msg1 and Msg3 can be transmitted and received as a single message (e.g., MsgA), and / or Msg2 and Msg4 can be transmitted and received as a single message (e.g., MsgB).

[0048] 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 controlling the connection (e.g., a radio resource control (RRC) layer), a layer handling mapping between a logical channel and a transmission channel (e.g., a media access control (MAC) layer), and a layer handling a physical channel (e.g., a physical (PHY) layer). For example, the first device and the second device may perform at least one of signaling to establish a connection, signaling to determine settings related to communication, and / or signaling to indicate allocated resources. For example, the control information may be signaled / transmitted through 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.

[0049] 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 data based on signaling of control information and transmit and / or receive it. 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, antenna-specific waveform demodulation, signal placement considering layer mapping, constellation demapping, descrambling, and / or channel decoding.

[0050] For example, the layers of the radio interface protocol between the first device and the second device can be classified into L1 (layer 1), L2 (layer 2), L3 (layer 3), etc. For example, the physical layer belonging to layer 1 can provide an information transfer service using a physical channel, and the radio resource control (RRC) layer located at layer 3 can perform the role of controlling radio resources between the first device and the second device. For example, to this end, the RRC layer can exchange RRC messages between the first device and the second device.

[0051] FIG. 2 illustrates a radio protocol architecture according to one 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 said embodiment may be omitted. For example, FIG. 2(a) may represent a radio protocol stack in the user plane for uplink communication or downlink communication, and FIG. 2(b) may represent a radio protocol stack in the control plane for uplink communication or downlink communication. For example, FIG. 2(c) may represent a radio protocol stack in the user plane for device-to-device communication, and FIG. 2(d) may represent a radio protocol stack in the control plane for device-to-device communication.

[0052] For example, the physical layer can provide information transmission services to upper layers using a physical channel. For example, the physical layer can be connected to the upper layer, the MAC (medium access control) layer, through a transport channel. For example, data can be transmitted between the MAC layer and the physical layer through a transport channel. For example, transport channels can be classified according to how and with what characteristics data is transmitted through a wireless interface. For example, data can be transmitted through a physical channel between different physical layers, for example, between the physical layers of a first device and a second device. For example, the physical channel can be modulated using the OFDM (orthogonal frequency division multiplexing) method, and time and frequency can be utilized as wireless resources.

[0053] For example, the MAC layer can provide services to the upper layer, the RLC (radio link control) layer, through logical channels. For example, the MAC layer can provide mapping functions from multiple logical channels to multiple transmission channels. For example, the MAC layer can provide logical channel multiplexing functions through mapping from multiple logical channels to a single transmission channel. For example, the MAC sublayer can provide data transmission services over logical channels.

[0054] For example, the RLC layer can perform concatenation, segmentation, and reassembly of RLC service data units (SDUs). For example, to guarantee various quality of service (QoS) required by a radio bearer (RB), the RLC layer can provide three modes of operation: transparent mode (TM), unacknowledged mode (UM), and acknowledged mode (AM). For example, AM RLC can provide error correction through automatic repeat requests (ARQ).

[0055] For example, the RRC (radio resource control) layer may be defined only in the control plane. For example, the RRC layer may be responsible for controlling logical channels, transmission channels, and physical channels in relation to the configuration, reconfiguration, and release of radio bearers. For example, RB may refer to a logical path provided by the first layer (e.g., physical layer) and the second layer (e.g., MAC layer, RLC layer, PDCP (packet data convergence protocol) layer, SDAP (service data adaptation protocol) layer, etc.) for data transfer between a first device and a second device.

[0056] For example, the functions of the PDCP layer in the user plane may include the delivery of user data, header compression, and ciphering. For example, the functions of the PDCP layer in the control plane may include the delivery of control plane data and encryption / integrity protection.

[0057] For example, the establishment of an RB can mean the process of defining the characteristics of the wireless protocol layer and channel to provide specific services, and setting each specific parameter and method of operation. For example, an RB can be divided into two types: an SRB (signaling radio bearer) and a DRB (data radio bearer). For example, an SRB can be used as a channel to transmit RRC messages in the control plane, and a DRB can be used as a channel to transmit user data in the user plane.

[0058] 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 is in the RRC_CONNECTED state, and if not, it may be in the RRC_IDLE state. For example, in the case of NR, an additional RRC_INACTIVE state is defined, and a terminal in the RRC_INACTIVE state maintains a connection with the core network while releasing the connection with the base station.

[0059] For example, a downlink transmission channel may include at least one of a broadcast channel (BCH) that transmits system information and / or a shared channel (SCH) that transmits user traffic or control messages. For example, traffic or control messages for a downlink multicast or broadcast service may be transmitted via a downlink SCH or via a separate multicast channel (MCH). Meanwhile, an uplink transmission channel may include at least one of a random access channel (RACH) that transmits initial control messages and / or a shared channel (SCH) that transmits user traffic or control messages. For example, a logical channel located above the 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).

[0060] FIG. 3 shows the structure of a wireless frame according to one 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.

[0061] Referring to FIG. 3, radio frames may be used, for example, 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 contain 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 by subcarrier spacing (SCS). For example, each slot may contain 12 or 14 OFDM(A) symbols according to a cyclic prefix (CP).

[0062] For example, when normal CP is used, each slot may contain 14 symbols. For example, when extended CP is used, each slot may contain 12 symbols. Here, for example, the symbols may include OFDM symbols (or CP-OFDM symbols) and SC-FDMA (single carrier-FDMA) symbols (or DFT-s-OFDM (Discrete Fourier Transform-spread-OFDM) symbols).

[0063] Table 2 below shows the number of symbols per slot (N) according to 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 ) exemplifies.

[0064] CP Type SCS (15*2 u )N slot symb N frame,u slot N subframe,u slotNormal CP 15kHz (u=0) 1410 130kHz (u=1) 1420 260kHz (u=2) 1440 4120kHz (u=3) 1480 8240kHz (u=4) 14160 16 Extended CP 60kHz (u=2) 1240 4

[0065] For example, OFDM(A) numerology (e.g., SCS, CP length, etc.) may be configured differently among multiple cells merged into a single terminal. Accordingly, the (absolute time) interval of a time resource (e.g., subframe, slot, or TTI (transmit time interval)) composed of the same number of symbols may be configured differently among the merged cells. For example, in the present disclosure, time resources such as subframes, slots, TTI, etc. may be referred to as time units.

[0066] For example, multiple numerologies or SCSs may be supported to support various services. For example, if the SCS is 15 kHz, a wide area in traditional cellular bands may be supported, and if the SCS is 30 kHz / 60 kHz, dense-urban, lower latency, and wider carrier bandwidth may be supported. For example, if the SCS is 60 kHz or higher, a bandwidth greater than 24.25 GHz may be supported to overcome phase noise.

[0067] FIG. 4 shows a slot structure of a frame according to one 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, suggestions, methods, and / or operations of the embodiments may be omitted.

[0068] 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 a single numerology (e.g., SCS, CP length, etc.). For example, a carrier may include up to N BWPs (where N is a positive integer). For example, data communication may be performed through an active BWP. For example, each element may be referred to as a resource element (RE) in a resource grid and may be mapped to a single complex symbol.

[0069] For example, a BWP can be a continuous set of PRBs in a given numerology. For example, a PRB can be selected from a continuous subset of common resource blocks (CRBs) for a given numerology on a given carrier.

[0070] For example, the BWP may be at least one of an active BWP, an initial BWP, and / or a default BWP. For example, the terminal may not monitor downlink radio link quality on DL BWPs other than the active DL BWP on the PCell (primary cell). For example, the terminal may not receive PDCCH (physical downlink control channel), PDSCH (physical downlink shared channel), or CSI-RS (channel state information-reference signal) (except for RRM (radio resource management)) outside of the active DL BWP. For example, the terminal may not trigger CSI (channel state information) reporting for an inactive DL BWP. For example, the terminal may not transmit PUCCH (physical uplink control channel) or PUSCH (physical uplink shared channel) outside of the active UL (uplink) BWP. For example, for the downlink, the initial BWP can be given as a consecutive set of resource blocks (RBs) for the remaining minimum system information (RMSI) CORESET (control resource set) (set by the physical broadcast channel (PBCH)). For example, for the uplink, 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 the upper layer. For example, the initial value of the default BWP can be the initial DL BWP.For energy saving, if the terminal fails to detect DCI (downlink control information) for a certain period, the terminal can switch the active BWP of the terminal to the default BWP.

[0071] 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.

[0072] Referring to FIG. 5, for example, a common resource block (CRB) may be a numbered carrier resource block from one end of the 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 the resource block grid.

[0073] For example, BWP is point A, offset from point A (N start BWP ) and bandwidth (N size BWP It can be set by ). For example, point A may be an external reference point of the PRB of a carrier where the subcarrier 0 of all numerologies (e.g., all numerologies supported by the network in that carrier) are aligned. For example, offset may be the PRB interval between the lowest subcarrier in a given numerology and point A. For example, bandwidth may be the number of PRBs in a given numerology.

[0074] FIG. 6 illustrates a communication structure that can be provided in a 6G system according to one 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 said embodiments may be omitted.

[0075] As core implementation technologies for 6G systems, technologies such as artificial intelligence (AI), THz (Terahertz) communication, optical wireless technology, free space optical transmission (FSO) backhaul networks, large-scale 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.

[0076] - Artificial Intelligence: Introducing AI into communications can streamline and enhance real-time data transmission. AI can determine how complex target tasks are performed using numerous analyses. For example, AI can increase efficiency and reduce processing latency. Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly using AI. AI can also play a significant role in M2M, machine-to-human, and human-to-machine communication. Furthermore, AI can enable rapid communication in Brain-Computer Interfaces (BCI). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0077] - THz Communication: Data transmission rates can be increased by expanding bandwidth. This can be achieved by using sub-THz communication with wide bandwidth and applying advanced large-scale MIMO technology. THz waves, also known as sub-millimeter radiation, generally refer to a frequency band between 0.1 THz and 10 THz with corresponding wavelengths ranging from 0.03 mm to 3 mm. The 100 GHz-300 GHz band range (Sub-THz band) is considered the primary portion of the THz band for cellular communication. Adding the Sub-THz band to the mmWave band increases 6G cellular communication capacity. Among the defined THz bands, the 300 GHz-3 THz band is located in the far-infrared (IR) frequency band. Although the 300 GHz-3 THz band is part of the optical band, it lies at the boundary of the optical band and immediately following the RF band. Therefore, this 300 GHz-3 THz band exhibits similarities to RF. Key characteristics of THz communication include (i) widely available bandwidth to support very high data transmission rates, and (ii) high path loss occurring at high frequencies (highly directional antennas are indispensable). The narrow beam width generated by highly directional antennas reduces interference. The small wavelength of THz signals allows a much larger number of antenna elements to be integrated into devices and BSs operating in this band. This enables the use of advanced adaptive array technologies that can overcome range limitations.

[0078] - Large-scale MIMO technology

[0079] - Hologram beamforming (HBF)

[0080] - Optical wireless technology

[0081] - Free Space Optical Transmission Backhaul Network (FSO backhaul network)

[0082] - Quantum communication

[0083] - Cell-free communication

[0084] - Integration of wireless information and power transmission

[0085] - Integration of wireless communication and sensing

[0086] - Integrated access and backhaul network

[0087] - Big data analysis

[0088] - Reconfigurable intelligent metasurface

[0089] - Metaverse

[0090] - blockchain

[0091] - Advanced Air Mobility (AAM): AAM can be a broad concept encompassing Urban Air Mobility (UAM), Regional Air Mobility (RAM), and Unmanned Aerial Systems (UAS). For example, AAM may include UAM, RAM, UAS, and UAVs (unmanned aerial vehicles).

[0092] - Autonomous driving (self-driving): V2X (vehicle to everything), a core element of building autonomous driving infrastructure, refers to technologies that enable vehicles to communicate and share with various elements on the road to perform autonomous driving, such as wireless communication between vehicles (vehicle to vehicle, V2V) and between vehicles and infrastructure (vehicle to infrastructure, V2I).

[0093] - Non-terrestrial Network (NTN): An NTN may refer to a network or network segment that utilizes RF (radio frequency) resources mounted on a satellite (or UAS platform). The use of NTN services may be considered to secure wider coverage or to provide wireless communication services in locations where the installation of wireless communication base stations is difficult.

[0094] - 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.

[0095] - Reconfigurable Intelligent Surface (RIS): An RIS can be used to manipulate and enhance signal propagation in a wireless communication environment. For example, an 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 instance, an RIS can improve signal reception by controlling the path, phase, and / or strength of the propagating signal. For instance, power consumption can be very low because power is consumed only for controlling the phase and amplitude of the small antennas. For instance, since an RIS can be reconfigured to suit various environments, it can meet diverse communication requirements and operate effectively in dynamic network environments.

[0096] 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.

[0097] Referring to FIG. 7, NTN communication can be performed based on a satellite network, HIBS (high-altitude platform stations (HAPS) as international mobile telecommunications (IMT) base stations (BS)), and an aeronautical communication-capable terminal (e.g., AAM). For example, to improve coverage, devices such as a satellite network, HIBS, and an aeronautical communication-capable terminal (e.g., AAM) 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.

[0098] For example, a terminal can obtain information about the characteristics of the environment and / or 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 capabilities do not require connecting to an object via a device within the network, they can provide services for object location determination without a device. The ability to obtain range, velocity, and angle information from radio frequency signals can provide a wide range of new functions, such as various object detection, object recognition (e.g., vehicles, humans, animals, UAVs), and high-precision localization, tracking, and activity recognition. Radio sensing services can provide information to various industries (e.g., unmanned aerial vehicles, smart homes, V2X, factories, railways, public safety, etc.) that enable applications such as intruder detection, assisted vehicle steering and navigation, trajectory tracking, collision avoidance, traffic management, and health and traffic management. In some cases, radio sensing may use non-3GPP type sensors (e.g., radar, cameras) to further support 3GPP-based sensing. For example, the operation of a wireless sensing service, e.g., sensing operation, may depend on the transmission, reflection, and scattering processing of wireless sensing signals. Therefore, wireless sensing can provide an opportunity to enhance existing communication systems from communication networks into wireless communication and sensing networks.

[0099] FIG. 8 illustrates an example of a sensing operation according to an embodiment of the present disclosure. The embodiment of FIG. 8 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, suggestions, methods, and / or operations of the embodiments may be omitted. Specifically, FIG. 8 (a) illustrates an example of sensing using a sensing receiver and a sensing transmitter located at the same location (e.g., monostatic sensing), and FIG. 8 (b) illustrates an example of sensing using a separated sensing receiver and a sensing transmitter (e.g., bistatic sensing).

[0100] Referring to FIG. 8, a sensing transmitter may transmit a sensing signal for sensing one or more objects (and / or the environment surrounding the objects). For example, the sensing signal may be a radio (frequency) signal defined to be transmittable by a base station / terminal. For example, a sensing receiver may receive a signal that is scattered or reflected by one or more objects (and / or the environment surrounding the objects) from the sensing signal transmitted by the sensing transmitter. For example, at the sensing receiver, sensing data may be derived from the scattered or reflected signal, and a sensing result may be generated or obtained through processing of the sensing data. Here, for example, the sensing result may include characteristic information (e.g., location, distance, speed, angle, etc.) about one or more objects (and / or the environment surrounding the objects). For example, the sensing results generated / acquired in this way may be utilized for wireless sensing services (e.g., detection, tracking of objects and / or environments, etc.) or provided / disclosed to a trusted third party.

[0101] For example, a sensing transmitter may be a base station or terminal that transmits a sensing signal to be used for the operation of a sensing service, and the sensing transmitter may be located at the same base station or terminal as the sensing receiver or at a different base station or terminal. For example, a sensing receiver may be a base station or terminal that receives a sensing signal to be used for the operation of a sensing service, and the sensing receiver may be located at the same base station or terminal as the sensing transmitter or at a different base station or terminal. For example, a sensing target may be an object to be detected by deriving the characteristics of an object within the environment from the 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 that of a sensing target. For example, monostatic sensing may be a sensing in which the sensing transmitter and the sensing receiver coexist at the same base station or terminal. For example, bistatic sensing may be sensing where the sensing transmitter and the sensing receiver are located at different base stations or terminals. For example, multistatic sensing may be sensing where 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 below 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 above or equal to a threshold, it may be defined as bistatic sensing or multistatic sensing.For example, the terminal can transmit a sensing signal over a wireless interface that can be used for sensing purposes. For example, the terminal can transmit a sensing signal over a 3GPP wireless interface that can be used for sensing purposes.

[0102] Meanwhile, in conventional communications (e.g., NR Uu or NR sidelink), the sensing procedure of a device (e.g., terminal or base station) was not considered a service. However, since the primary purpose of an ISAC service is to rapidly detect and distinguish a target object (e.g., target object) through sensing, the sensing procedure (or operation) needs to be classified as a service that must satisfy a QoS requirement (e.g., sensing latency: the time required for a terminal triggering the sensing procedure to receive the sensing result of the target object from a receiving terminal, sensing accuracy, etc.). For example, in ISAC, the sensing operation of a device (e.g., terminal, base station, or SMF (sensing management function)) can be considered a service that must satisfy the QoS requirement related to ISAC sensing, and the terminal can perform a sensing operation based on the corresponding sensing QoS (e.g., transmitting a sensing RS and / or receiving a sensing RS).

[0103] For example, in ISAC, sensing can be considered a higher-tier service that must satisfy sensing result-based sensing QoS (or sensing quality), and a new QoS for ISAC sensing services (e.g., Sensing QoS Flow ID, SQFI) can be defined as follows. For example, SQFI can be set to a value from 1 to 8. For example, SQFI can be distinguished according to the level of sensing QoS requirements (e.g., sensing accuracy, sensing latency: the delay bound from triggering sensing until receiving the sensing result, sensing priority: e.g., a priority that can be used to determine which sensing service is triggered first based on priority when multiple sensing procedures are required). For example, a smaller SQFI value can be defined as a sensing service with tighter QoS requirements (e.g., a sensing service requiring high sensing accuracy or a sensing service requiring low / lower / lowest sensing latency). For example, a sensing service with a larger SQFI value can be defined as having tighter QoS requirements (e.g., a sensing service requiring high sensing accuracy or a sensing service requiring low / lower / lowest sensing latency).

[0104] Additionally, in ISAC, terminal and TRP (or base station) operations for supporting sensing services such as detection, localization, and tracking may be defined. For example, the sensing QoS for ISAC services (detection, localization, tracking, etc.) may be as follows.

[0105] - Detection QoS: Detection probability, False alarm probability

[0106] - Location Finding QoS: Finding the location of static objects. Location Finding QoS parameters (time delay, angle of reach)

[0107] - Tracking QoS: Tracks changes in the state (distance, angle, speed, etc.) of moving objects (e.g., vehicles or drones).

[0108] For example, a support scenario for sensing services in an ISAC could be as follows. Here, for example, the network could be a gNB.

[0109] FIG. 9 illustrates an example of six sensing scenarios for a sensing service according to an embodiment of the present disclosure. Specifically, FIG. 9(a) illustrates an example of gNB monostatic, FIG. 9(b) illustrates an example of gNB bistatic, and FIG. 9(c) illustrates an example of gNB-UE bistatic. Additionally, FIG. 9(d) illustrates an example of UE-gNB bistatic, FIG. 9(e) illustrates an example of UE monostatic, and FIG. 9(f) illustrates an example of UE bistatic. An embodiment of FIG. 9 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.

[0110] Referring to Fig. 9, for example, six sensing scenarios for a sensing service in ISAC may be as follows.

[0111] For example, six principal sensing modes:

[0112] - gNB monostatic (the same gNB performs both the transmitter (Tx) and receiver (Rx)

[0113] - gNB bi-static (one gNB is the transmitter (Tx) and the other gNB is the receiver (Rx)

[0114] - gNB-to-UE bi-static (gNB is the transmitter (Tx) and UE is the receiver (Rx)

[0115] - UE-to-gNB bi-static (UE is the transmitter (Tx) and gNB is the receiver (Rx)

[0116] - UE Monostatic (The same UE performs both the transmitter (Tx) and receiver (Rx)

[0117] - UE bi-static (One UE is the transmitter (Tx) and the other UE is the receiver (Rx)

[0118] Meanwhile, conventional NR systems support CP (control plane) and UP (user plane) for the transmission of communication service-related data, thereby providing data delivery services (e.g., NAS messages, RRC messages, user data messages). For example, in an NR system, CP is used for RRC and NAS signaling, and UP is used as a transmission path for user data. However, in 6G, AI-based decision results generated by terminals, environmental awareness data, and real-time sensing data in milliseconds have small and high-frequency transmission characteristics, making efficient transmission difficult with general UP processing. Therefore, there is a need to propose a method for efficiently transmitting 6G services / data and a device that supports it.

[0119] FIG. 10 illustrates a QoS model for a communication service 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] The embodiment of FIG. 10 may represent a QoS model (e.g., QoS flow to DRB mapping) for supporting communication services (e.g., uplink transmission, downlink transmission, uplink reception, downlink reception) in a conventional 5G system. For example, as in the embodiment of FIG. 10, a user plane function (UPF), which is an entity of the core network, can map service data flows (e.g., Video, VoIP, Best Effort, etc.) received from a data network (DN) to (each) QoS flows. For example, the UPF can organize one or more QoS flows into a single PDU session. For example, a gNB (or the SDAP of the gNB) can map the QoS flows for service data received from the UPF to a DRB. In this case, for example, the gNB (or the SDAP of the gNB) can map one QoS flow to one DRB or map multiple QoS flows to one DRB.

[0121] In the following description, various names are exemplary and may be considered to perform the same or similar functions (regardless of their names) based on the content described in each step.

[0122] In the present disclosure, for example, the following terms may be used.

[0123] - LMF: Location management function

[0124] - UE-triggered SL positioning: SL (sidelink) positioning where the procedure is triggered by the UE

[0125] - SL positioning triggered by base station / LMF: SL positioning where the procedure is triggered by base station / LMF

[0126] - UE-controlled SL positioning: SL positioning where the SL positioning group is generated by the UE

[0127] - SL positioning controlled by a base station: SL positioning where the SL positioning group is generated by the base station

[0128] - UE-based SL positioning: SL positioning where the UE location is calculated by the UE

[0129] - UE-assisted SL positioning: SL positioning where the UE location is calculated by the base station / LMF

[0130] - SL Positioning Group: UEs participating in SL positioning

[0131] - T-UE(Target UE): UE whose position is calculated

[0132] - S-UE (Server UE): A UE that assists T-UE's positioning

[0133] - Anchor UE: A UE that assists T-UE's positioning

[0134] - MG: Measurement gap where only SL PRS transmission is allowed

[0135] - MW: Measurement window where both SL data and SL PRS can be transmitted in a multiplexed way

[0136] - PRS: Positioning Reference Signal

[0137] - SL PRS: Sidelink Positioning Reference Signal

[0138] - CCH: control channel

[0139] - IUC (Inter-UE coordination) message: A message received by the TX UE from other UEs, including the RX UE, which contains information about the set of preferred resources suitable for the TX UE to transmit to the RX UE, and / or information about the set of non-preferred resources not suitable for transmission.

[0140] - UE-based: The way a UE calculates its own location is described as "UE-based".

[0141] - TP (transmission point): A set of transmission antennas (e.g., an antenna array having one or more antenna elements) placed at geographically identical locations for a cell, a part of a cell, or a DL PRS-only TP. Transmission points may include base station (ng-eNB or gNB) antennas, remote radio heads, remote antennas of base stations, antennas of DL PRS-only TPs, etc. A cell may include one or more transmission points. In the case of homogeneous placement, each transmission point may correspond to one cell.

[0142] - RP (reception point): A set of receiving antennas (e.g., antenna arrays having one or more antenna elements) placed at geographically identical locations for a cell, a part of a cell, or a UL SRS (sounding reference signal)-only RP. Reception points may include base station (ng-eNB or gNB) antennas, remote radio heads, remote antennas of base stations, antennas of UL SRS-only RPs, etc. A cell may include one or more reception points. In the case of homogeneous placement, each reception point may correspond to one cell.

[0143] - PRS-only TP: A TP that transmits only PRS signals for PRS-based TBS (terrestrial beacon system) positioning and is not connected to a cell.

[0144] - TRP (transmission-reception point): A set of antennas (e.g., an antenna array (with one or more antenna elements)) placed at the same geographical location that supports TP and / or RP functions.

[0145] - SRS-only RP: An RP that receives only SRS signals for UL-only positioning and is not associated with a cell

[0146] - Sensing devices: UE and / or TRP, and / or sensing TX devices and / or sensing RX devices

[0147] - Sensing TX device: A device that transmits a sensing reference signal

[0148] - Sensing RX device: A device that receives a sensing reference signal, and / or a device that monitors the sensing reference signal to perform a sensing measurement.

[0149] - Sensing signal: A sensing reference signal and / or a sensing measurement report; a reference signal transmitted and received for sensing; may be a transmission on the 3GPP radio interface that can be used for sensing purposes.

[0150] - Sensing transmitter: An entity that transmits a sensing signal; a sensing transmitter may be the entity that transmits the sensing signal which the sensing service will use in its operation. A sensing transmitter may be an NR RAN node or a UE. A sensing transmitter can be located in the same entity as the sensing receiver or in a different entity.

[0151] - Sensing receiver: An entity that receives a sensing signal; a sensing receiver may be an entity that receives the sensing signal which the sensing service will use in its operation. A sensing receiver may be an NR RAN node or a UE. A sensing receiver can be located in the same entity as the sensing transmitter or in a different entity.

[0152] - Sensing Server (SF (Sensing Function) or SMF (Sensing Management Function)): This is a server that controls sensing transmitters and receivers and oversees sensing operations and procedures. It can be considered to perform functions similar to those of a location management function (LMF) in positioning.

[0153] - SF (sensing function): A network entity that controls and manages the sensing procedures of a UE or TRP in the ISAC. For example, the SF can receive reports of sensing data collected by the UE or TRP and store the sensing data, and / or provide the sensing data for the sensing service to the sensing device.

[0154] - Monostatic sensing: Sensing where the sensing transmitter and sensing receiver are co-located in the same TRP or UE.

[0155] - Bistatic sensing: Sensing where the sensing transmitter and sensing receiver are located in different TRPs or different UEs.

[0156] - Multi-static sensing: Sensing in which multiple sensing transmitters and / or multiple sensing receivers exist for a single sensing target.

[0157] - BS-BS sensing: Sensing in which BS#1 transmits a sensing reference signal (sensing RS) and BS#2 receives the sensing RS. If BS#1 and BS#2 are separate BSs, it may mean BS-BS bistatic sensing operation, and if BS#1 and BS#2 are the same BS, it may mean BS-BS monostatic sensing operation. The BS may be a base station or a TRP (transmission and reception point). If BS#1 and / or BS#2 are one or more BSs, it may mean BS-BS multi-static sensing operation. The BS may mean a base station or a TRP (Transmission and Reception Point). (Sensing in which BS#1 transmits a sensing reference signal (RS) and BS#2 receives the sensing RS. When BS#1 and BS#2 are different base stations, the operation may correspond to BS-BS bistatic sensing, and when BS#1 and BS#2 are the same base station, the operation may correspond to BS-BS monostatic sensing. The BS may be a base station or a transmission and reception point (TRP). When BS#1 and / or BS#2 include one or more base stations, the operation may correspond to BS-BS multi-static sensing.)

[0158] - BS-UE bistatic sensing: Sensing in which a BS transmits a sensing reference signal (sensing RS) and a UE receives the sensing RS. The BS may be a base station or a transmission and reception point (TRP). If the BS and / or the UE include one or more BSs and / or one or more UEs, the operation may refer to BS-UE multistatic sensing. The BS may refer to a base station or a TRP.

[0159] - UE-BS bistatic sensing: Sensing in which a UE transmits a sensing reference signal (sensing RS) and a BS receives the sensing RS. The BS may be a base station or a transmission and reception point (TRP). If the BS and / or the UE include one or more BSs and / or one or more UEs, the operation may refer to UE-BS multistatic sensing. The BS may refer to a base station or a TRP.

[0160] - UE-UE sensing: Sensing in which UE#1 transmits a sensing reference signal (sensing RS) and UE#2 receives the sensing RS. If UE#1 and UE#2 are separate UEs, it may mean UE-UE bistatic sensing operation, and if UE#1 and UE#2 are the same UE, it may mean UE-UE monostatic sensing operation. The BS may be a base station or a transmission and reception point (TRP). If UE#1 and / or UE#2 are one or more UEs, it may mean UE-UE multistatic sensing operation. (Sensing in which UE#1 transmits a sensing RS and UE#2 receives the sensing RS. When UE#1 and UE#2 are different UEs, the operation may correspond to UE-UE bistatic sensing, and when UE#1 and UE#2 are the same UE, the operation may correspond to UE-UE monostatic sensing. When UE#1 and / or UE#2 include one or more UEs, the operation may correspond to UE-UE multi-static sensing.)

[0161] - Target object (TO): An object to be detected through sensing.

[0162] - TSA: Target sensing area. An area in which an object is intended to be detected through sensing.

[0163] - Moving TSA (target sensing area): A case where the target sensing service area moves according to the mobility of the target from the perspective of the sensing transmitter.

[0164] - Non-3GPP Sensing Data: Sensing data that is not collected through 3GPP communication-based sensing (e.g., camera data, video data, data collected through other RAT (e.g., Wi-Fi) based sensing, etc.)

[0165] - 3rd party entity: A server device operated by a sensing service operator (a business operator that uses / operates sensing data for a sensing service). For example, the 3rd party entity may receive and store sensing data for a sensing service from a sensing device, and / or provide sensing data for a sensing service to a sensing device.

[0166] For example, an SL PRS transmission resource may be composed of an SL PRS resource set consisting of the following information.

[0167] - SL PRS resource set ID

[0168] - SL PRS Resource ID List: List of SL PRS resource IDs within the SL PRS resource set

[0169] - SL PRS Resource Type: Can be set to periodic, aperiodic, semi-persistent, or on-demand

[0170] - Alpha for SL PRS power control

[0171] - P0 for SL PRS power control

[0172] - Path loss reference for SL PRS power control: Can be set to SL SSB, DL PRS, UL SRS, UL SRS for positioning, PSCCH DMRS, PSSCH DMRS, PSFCH, SL CSI RS, etc.

[0173] For example, the above SL PRS resource set may be composed of SL PRS resources consisting of the following information.

[0174] - SL PRS Resource ID

[0175] - SL PRS Comb Size: The interval between REs transmitted within a symbol for SL PRS.

[0176] - SL PRS Comb Offset: The RE index where the SL PRS within the first SL PRS symbol is first transmitted.

[0177] - SL PRS Comb Cyclic Shift: A cyclic shift used to generate the sequence that constitutes the SL PRS

[0178] - SL PRS start position: Index of the first symbol transmitting the SL PRS within a single slot

[0179] - Number of SL PRS symbols: The number of symbols constituting the SL PRS within a single slot

[0180] - Frequency domain shift: The lowest frequency position (index) in the frequency domain where the SL PRS is transmitted

[0181] - SL PRS BW: Frequency bandwidth used for SL PRS transmission

[0182] - SL PRS Resource Type: Can be set to periodic, aperiodic, semi-persistent, or on-demand

[0183] - SL PRS Periodicity: The period in the time domain between SL PRS resources, physical, or the unit of a logical slot in the resource pool where SL PRS is transmitted.

[0184] - SL PRS Offset: An offset in the time domain from the reference timing to the start of the first SL PRS resource, in units of physical or logical slots within 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 the RRC / MAC-CE / DCI / SCI associated with the SL PRS resource.

[0185] - SL PRS Sequence ID

[0186] - SL PRS spatial relation: Can be set to SL SSB, DL PRS, UL SRS, UL SRS for positioning, PSCCH DMRS, PSSCH DMRS, PSFCH, SL CSI RS, etc.

[0187] - SL PRS CCH: SL PRS control channel. Can signal SL PRS resource configuration information and resource locations, etc.

[0188] In this disclosure, TRP and base station may be substituted and used as the same entity. In this disclosure, the term "sensing message" may be a term that can be used interchangeably with "sensing reference signal" or "sensing measurement report." The sensing signal mentioned in this disclosure may be interpreted as having the same meaning as the sensing reference signal. The sensing data mentioned in this disclosure may be interpreted as having the same meaning as the sensing measurement data or the sensing measurement report. The bandwidth part (BWP) mentioned in this disclosure may be substituted and applied as a bandwidth setting set or a wireless resource set, etc. The wireless resource profile exemplified in this disclosure may be substituted and applied as a bandwidth part (BWP), a bandwidth setting set, or a wireless resource set, etc.

[0189] In the present disclosure, for example, the following terms may be defined to describe AI / ML.

[0190] - Data collection: Data collected from network nodes, management entities, or terminals, serving as a basis for ML model training, data analysis, and inference.

[0191] - ML Model: A data-driven algorithm that applies machine learning techniques to generate a set of outputs containing predictive information based on a set of inputs.

[0192] - ML Training: An online or offline process of training an ML model by learning features and patterns that best represent the data and acquire an ML model trained for inference.

[0193] - ML Inference: A process of making predictions or deriving decisions based on collected data and ML models using a trained ML model.

[0194] FIG. 11 illustrates a functional framework for artificial intelligence and machine learning (AI / ML) according to one 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 said embodiment may be omitted.

[0195] Referring to FIG. 11, for example, data collection may be a function that provides input data to model training and model inference functions. AI / ML algorithm-specific data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) may not be performed in the data collection function. Examples of input data may include measurements from terminals or other network entities, feedback from actors, and outputs from AI / ML models.

[0196] For example, training data may be data required as input for the training function of an AI / ML model.

[0197] For example, inference data may be data required as input for the inference function of an AI / ML model.

[0198] For example, model training may be a function that performs ML model training, validation, and testing to generate model performance metrics as part of the model testing procedure. If necessary, the model training function may also be responsible for data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) based on training data provided by the data collection function.

[0199] For example, model deployment / update can be used to initially deploy trained, validated, and tested AI / ML models to the model inference function, or to provide updated models to the model inference function.

[0200] For example, model inference can be a function that provides AI / ML model inference outputs (e.g., predictions or decisions). Where applicable, the model inference function can provide model performance feedback to the model training function. If necessary, the model inference function can also handle data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) based on the inference data provided by the data collection function.

[0201] For example, the output may be the inference output of an AI / ML model generated by the model inference function. Note that the details of the inference output may vary depending on the use case.

[0202] For example, model performance feedback can be used to monitor the performance of AI / ML models.

[0203] For example, an actor can be a function that receives output from a model inference function and triggers or performs the corresponding action. An actor can trigger actions on other entities or on itself.

[0204] For example, feedback may be information that is necessary to derive training or inference data or performance feedback.

[0205] For example, in datasets used in AI / ML, the definitions of training, validation, and test data can be as follows. For instance, training data may be a dataset for training a model. For instance, validation data may be a dataset for validating a model that has already been trained. For instance, validation data is typically used to prevent overfitting of the training dataset. For instance, validation data may be a dataset for selecting the best model among several models trained during the learning process. Therefore, this can be viewed as a type of training. For instance, test data may be a dataset for final evaluation, and test data may be unrelated to training. For instance, regarding the above datasets, if the training set is divided, the training and validation data within the entire training set can typically be split in a ratio of approximately 8:2 or 7:3; if tests are included, the ratio can be split as 6:2:2 (training:validation:test).

[0206] For example, in the present disclosure, "specific threshold" may mean a threshold that is predefined or (pre-)set by an upper layer (including the application layer) of a network, base station, or terminal. For example, in the present disclosure, "specific set value" may mean a value that is predefined or (pre-)set by an upper layer (including the application layer) of a network, base station, or terminal. For example, in the present disclosure, "set by the network / base station" may mean an action in which a base station sets to a UE (pre-) through upper layer RRC signaling, sets / signals to a UE through MAC CE, or signals to a UE through DCI.

[0207] For example, in the present disclosure, a message may be interpreted as being replaced by at least one of a control message, a data message, a signal, a data signal, and / or a control signal.

[0208] In the following description, various names are exemplary and may be considered to perform the same or similar functions (regardless of their names) based on the content described in each step.

[0209] For example, in this disclosure, various names are exemplary and may be replaced or considered as other names performing the same or similar functions based on the content described in each step (regardless of the name).

[0210] For example, a wide bandwidth allocation behavior (e.g., or a UE reporting-based bandwidth setting behavior) to support AI / ML operations in 6G communication may be proposed.

[0211] For example, in 6G, it may be necessary to support advanced services such as autonomous driving, smart cities, industrial automation, digital twins, and real-time environmental sensing through Integrated Sensing and Communication (ISAC), where communication and sensing are converged. Furthermore, as AI / ML-based automation and optimization technologies are applied across the network, 6G may require a much wider bandwidth than existing 5G NR communication. For instance, in sensing, using a wider bandwidth allows for more accurate measurement of location and distance information, and utilizing a wider frequency band enables more precise Doppler effect analysis, leading to more accurate detection of the speed and movement of target objects. Additionally, for instance, the bandwidth of 5G NR communication may have limitations in rapidly transmitting the large volumes of high-resolution data required for AI / ML model training or model inference.

[0212] The present disclosure relates to sensing and AI / ML (artificial intelligence / machine learning) based communication, and more specifically, to a method for efficiently allocating resources for large-capacity data transmission related to sensing and AI / ML by having a terminal provide information related to sensing resolution, mobility, data demand, etc., to a base station by including such information in assistance information.

[0213] In existing NR (New Radio) systems, even though sensing or AI / ML-based services generate new forms of high-volume data traffic, there was a lack of a structure that allowed terminals to notify base stations in advance of the characteristics of such traffic or the amount of resources required. As a result, base stations found it difficult to secure resources suitable for the characteristics of sensing services (e.g., resolution, detection range, movement speed, etc.) in advance, and consequently, unnecessary resource waste or a degradation of Quality of Service (QoS) due to resource shortages occurred.

[0214] Accordingly, the objective of the present disclosure is to provide a method that enables a base station to preemptively allocate resources necessary for sensing and AI / ML-related services by having a terminal provide sensing-related information, such as sensing resolution, movement speed, target detection range, and AI / ML data requirements, as auxiliary information.

[0215] For example, to overcome the same problem for the above in 6G, the present disclosure proposes a bandwidth setting and allocation operation for a network based on service-related reporting information of a terminal (e.g., a base station or a sensing function responsible for managing / collecting / inferencing sensing data or a network entity for supporting AI / ML operations) as follows.

[0216] For example, Proposal 1) Terminal reporting information and reporting procedure for wide bandwidth allocation requests to improve sensing accuracy in ISAC

[0217] For example, in general communication (e.g., LTE, NR), base stations allocate transmission resources to terminals by reflecting the QoS requirements of the transmitted data, but in sensing, sensing detection performance and sensing accuracy may be more important factors than QoS. Therefore, for example, when allocating transmission resources for a sensing signal (e.g., a sensing reference signal), it may be necessary to allocate transmission resources for the sensing signal by considering sensing detection performance and sensing accuracy rather than QoS. Accordingly, for example, in the present disclosure, a sensing device may report the following information to a base station for the allocation of resources for the transmission of a sensing signal by a sensing TX device (e.g., a sensing device that transmits a sensing signal) to allocate a wide bandwidth to improve sensing accuracy.

[0218] FIG. 12 illustrates an example of a reporting procedure 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, suggestions, methods, and / or operations of the embodiments may be omitted.

[0219] Referring to FIG. 12, for example, at step S1210, the first device may establish an RRC connection with the second device. For example, step S1210 may be omitted. For example, at step S1220, the first device may transmit auxiliary information to the second device. For example, the auxiliary information is an example of a term and is not limited to that term. For example, the auxiliary information may be transmitted to the second device in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, the first device may be a sensing device (e.g., a sensing TX device or a sensing RX device). For example, the second device may be a base station or a sensing function.

[0220] - For example, information reported for resource allocation for sensing

[0221] - - For example, sensing resolution requirement information

[0222] For example, a sensing device (e.g., a sensing TX device or a sensing RX device) may report sensing resolution requirement information (e.g., high resolution, high resolution, low resolution) for a triggered sensing service to a base station or a sensing function. For example, the base station or the sensing function may allocate bandwidth to the sensing device for transmitting / receiving a sensing signal (e.g., a sensing reference signal) based on the sensing resolution requirement information.

[0223] - - - for example,

[0224] - - - - For example, 1) high resolution

[0225] For example, a base station or a sensing function can set or switch a wider bandwidth part to a sensing device. For example, it can set a wider bandwidth resource (e.g., allocate a wider bandwidth resource within the same BWP).

[0226] - - - - For example, 2) high resolution

[0227] For example, a base station or a sensing function can set or switch a bandwidth part between a wider bandwidth part and a narrow bandwidth part in a sensing device. For example, it can set a bandwidth resource between a wider bandwidth and a narrow bandwidth (for example, allocate a bandwidth resource between a wider bandwidth and a narrow bandwidth resource within the same BWP).

[0228] - - - - For example, 3) low resolution

[0229] For example, a base station or a sensing function may set or switch a narrow bandwidth part to a sensing device (e.g., switching from a wide BWP to a narrow BWP). For example, or, a base station or a sensing function may set a narrow bandwidth resource (e.g., allocating a narrow bandwidth resource within the same BWP).

[0230] - - - - For example, 4) Although high / medium / low resolution requirement information has been described as an example in this disclosure, the sensing device may transmit resolution requirements of various values ​​to a base station or a sensing function, and based on the sensing resolution requirement information transmitted by the sensing device, the base station or the sensing function may set (or switch) an appropriate bandwidth part or allocate bandwidth to the sensing device.

[0231] For example, the sensing resolution requirement information may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when the sensing resolution requirement information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this required sensing resolution MAC CE be higher than the data from any logical channel, except data from UL-CCCH, and lower than the MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channel of the required sensing resolution MAC CE be lower than the priority of the data from the Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0232] For example, the relevant sensing resolution requirement information can also be transmitted to the base station by the sensing function based on the sensing service information.

[0233] According to an embodiment of the present disclosure, for example, the unambiguous target detection range has a characteristic proportional to the period or interval of the sensing signal. For example, when a terminal reports the target detection range to a base station, the terminal can set and adjust the period or interval of the sensing signal resource mapped to the target detection range based on the base station's information. For example, if the target detection range is to be increased, the period or interval of the sensing signal resource can be adjusted in a direction that increases, and in the opposite case, the period or interval can be set in a direction that decreases.

[0234] - - For example, target detection range report

[0235] For example, a sensing device (e.g., a sensing TX device or a sensing RX device) can report a target detection range (e.g., long range detection, medium range detection, short range detection) for a triggered sensing service (or for transmitting a sensing signal) to a base station or a sensing function. For example, the base station or the sensing function can allocate bandwidth to the sensing device for transmitting / receiving a sensing signal (e.g., a sensing reference signal) based on the target detection range information.

[0236] - - - for example,

[0237] - - - - For example, 1) long range detection

[0238] For example, a base station or a sensing function can set or switch a wider bandwidth part to a sensing device. For example, or, a base station or a sensing function can set a wider bandwidth resource (e.g., allocate a wider bandwidth resource within the same BWP).

[0239] - - - - For example, 2) Medium range detection

[0240] For example, a base station or a sensing function may set or switch a bandwidth part between a wider bandwidth part and a narrow bandwidth part in a sensing device. For example, or, a base station or a sensing function may set a bandwidth resource between a wider bandwidth and a narrow bandwidth (for example, allocate a bandwidth resource between a wider bandwidth and a narrow bandwidth resource within the same BWP).

[0241] - - - - For example, 3) Short range detection

[0242] For example, a base station or a sensing function may set or switch a narrow bandwidth part to a sensing device (e.g., switching from a wide BWP to a narrow BWP). For example, or, a base station or a sensing function may set a narrow bandwidth resource (e.g., allocating a narrow bandwidth resource within the same BWP).

[0243] - - - - For example, 4) Although the present disclosure describes long / medium / short target detection range information as an example, the sensing device may transmit target detection range requirements of various values ​​to a base station or a sensing function, and based on the target detection range requirement information transmitted by the sensing device, the base station or the sensing function may set (or switch) an appropriate bandwidth part or allocate bandwidth to the sensing device.

[0244] For example, target detection range request information may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when sensing resolution request information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this target detection range MAC CE be higher than the data from any logical channel, except data from UL-CCCH, and lower than the MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channel of this target detection range MAC CE be lower than the priority of the data from Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0245] For example, the target detection range request information can also be transmitted to the base station by the sensing function based on the sensing service information.

[0246] According to an embodiment of the present disclosure, for example, the unambiguous target detection range has a characteristic proportional to the period or interval of the sensing signal. For example, when a terminal reports the target detection range to a base station, the terminal can set and adjust the period or interval of the sensing signal resource mapped to the target detection range based on the base station's information. For example, if the target detection range is to be increased, the period or interval of the sensing signal resource can be adjusted in a direction that increases, and in the opposite case, the period or interval can be set in a direction that decreases.

[0247] For example, a report on the movement speed (e.g., low speed or high speed) of a terminal or target sensing area (or target object).

[0248] For example, a sensing device (e.g., a sensing TX device or a sensing RX device) can report movement speed information (e.g., high movement speed, medium movement speed, low movement speed) of a sensing device (e.g., a sensing TX device or a sensing RX device) or a target sensing area (or target object) to a base station or a sensing function. For example, a base station or a sensing function may allocate bandwidth to a sensing device for transmitting / receiving a sensing signal (e.g., a sensing reference signal) based on the movement speed information of a sensing device (e.g., a sensing TX device or a sensing RX device) or a target sensing area (or a target object).

[0249] - - - for example,

[0250] - - - - For example, 1) high movement speed

[0251] For example, a base station or a sensing function may set or switch a narrow bandwidth part to a sensing device. For example, or, a base station or a sensing function may set a wider bandwidth resource (e.g., allocate a narrow bandwidth resource within the same BWP).

[0252] - - - - For example, 2) medium speed

[0253] For example, a base station or a sensing function may set or switch a bandwidth part between a wider bandwidth part and a narrow bandwidth part in a sensing device. For example, or, a base station or a sensing function may set a bandwidth resource between a wider bandwidth and a narrow bandwidth (for example, allocate a bandwidth resource between a wider bandwidth and a narrow bandwidth resource within the same BWP).

[0254] - - - - For example, 3) Low movement speed (or no mobility)

[0255] For example, a base station or a sensing function may set or switch a wide bandwidth part to a sensing device (e.g., switching from a narrow BWP to a wide BWP). For example, or, a base station or a sensing function may set a wide bandwidth resource (e.g., allocating a wide bandwidth resource within the same BWP).

[0256] - - - - For example, 4) Although high / medium / low speed information is described as an example in this disclosure, the sensing device may transmit various values ​​of speed information requirements to a base station or a sensing function, and based on the speed requirement information transmitted by the sensing device, the base station or the sensing function may set (or switch) an appropriate bandwidth part or allocate bandwidth to the sensing device.

[0257] For example, velocity request information may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when sensing resolution request information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this velocity Range MAC CE be higher than the data from any logical channel, except data from UL-CCCH, and lower than the MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channel of this velocity range MAC CE be applied with a lower priority than the data of Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0258] For example, the corresponding velocity range request information can also be transmitted to the base station by the sensing function based on the sensing service information.

[0259] - - - According to an embodiment of the present disclosure, for example, the velocity estimation of a target object also has a characteristic proportional to the period or interval of a sensing signal, so for example, when a terminal reports the velocity of a target object to a base station, etc.,

[0260] - - - - For example, 1) a base station, etc., can perform an operation to set and adjust the period or interval of a sensing signal resource based on the velocity information. For example, if you want to estimate the high velocity of a target object, the period or interval of the sensing signal resource can be adjusted in a direction of decreasing, and of course, in the opposite case, the period or interval can be set and adjusted in a direction of increasing.

[0261] - - - - For example, 2) or a base station, etc., can perform an operation to adjust the numerology (SCS) of the sensing signal. For example, if you want to estimate the high velocity of a target object, the SCS of the sensing signal can be adjusted in a direction that increases, and in the opposite case, the SCS can be adjusted in a direction that decreases.

[0262] - - For example, sensing traffic patterns

[0263] For example, a sensing device (e.g., a sensing TX device or a sensing RX device) can report sensing traffic pattern information to a base station or a sensing function to a triggered sensing service. For example, the base station or the sensing function can allocate bandwidth to the sensing device for transmitting / receiving a sensing signal (e.g., a sensing reference signal) based on the sensing traffic pattern information (e.g., a wide BWP or wide bandwidth can be allocated to the sensing device at times when sensing traffic is high. For example, or, the base station or the sensing function can allocate a narrow BWP or narrow bandwidth to the sensing device at times when only partial sensing traffic occurs).

[0264] For example, the sensing tripack pattern information may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when sensing resolution request information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this sensing traffic pattern MAC CE be higher than the data from any logical channel, except data from UL-CCCH, and lower than the MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channel of this sensing traffic pattern MAC CE be lower than the priority of the data of Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0265] For example, the sensing traffic pattern request information can also be transmitted to the base station by the sensing function based on the sensing service information.

[0266] - For example, bandwidth part setting and switching

[0267] For example, based on the reporting information proposed above, the base station and the sensing function may set a bandwidth part for transmitting / receiving sensing signals or switch the bandwidth part. For example, or

[0268] - For example, adjusting bandwidth within a bandwidth part

[0269] For example, based on the proposed reporting information, the base station and the sensing function can set the bandwidth for transmitting / receiving the sensing signal or adjust the bandwidth.

[0270] For example, Proposal 2) Terminal reporting information and reporting procedure for wide bandwidth allocation requests to rapidly transmit large amounts of high-resolution data required to support AI / ML operations

[0271] For example, in general communication (e.g., LTE, NR), base stations allocate transmission resources to terminals by reflecting the QoS requirements of the transmitted data; however, in 6G communication, information regarding the required amount of AI / ML model training / model inference computations or the speed of AI / ML model training and inference required for AI / ML-based communication can be as important a factor as QoS information. For example, to support AI / ML operations, there may be cases where a terminal momentarily requires a wide bandwidth, and the base station (gNB) may need to dynamically allocate or switch the BWP (bandwidth part) and bandwidth accordingly. Therefore, for example, in the present disclosure, a sensing device may report the following information to the base station for the allocation of wide bandwidth to improve sensing accuracy, for resource allocation for the transmission of AI / ML data of the terminal (e.g., the required amount of AI / ML model training and inference computations, information on the speed of AI / ML model training and inference, etc.).

[0272] - For example, terminal reporting information for wide bandwidth allocation requests to rapidly transmit large amounts of high-resolution data required to support AI / ML operations

[0273] For example, data collection data requirements

[0274] For example, requirements for AI / ML model training, model management, and model inference data (e.g., training data, monitoring data, inference data, inference output data) (or data collection data requirements or training data transmission requirements / monitoring data transmission requirements / inference data transmission requirements)

[0275] For example, when performing AI / ML model training, model management, and model inference functions at a base station or core network entity (e.g., a management entity for AI / ML support), there may be a need for a terminal to transmit large amounts of raw data required for AI / ML model training, model management, and inference of the base station or core network entity to the base station or core network entity. For example, the terminal may also transmit data requirement information for the terminal's AI / ML model training, model management, and model inference large volume data to the base station, so that the base station may switch to a wide BWP suitable for the large volume data or allocate a wide BWP (or enable the base station to reconfigure a bandwidth part to a wide bandwidth part suitable for the large volume data or allocate wide bandwidth resources).

[0276] For example, information on AI / ML model training, model management, and model inference data / model inference output data requirements (or data collection data requirements) can also be transmitted to the base station in MAC CE format or as a dedicated RRC message (e.g., UE assistance information). For example, when information regarding the demand for AI / ML model training, model management, and model inference data / model inference output data is transmitted to the MAC CE, it may be proposed that the priority order of the logical channel of this AI / ML model training and inference data demand report MAC CE (or AI / ML data collection MAC CE) be higher than the priority of the data from any logical channel, except data from UL-CCCH, and lower than the priority of the MAC CE for other UU communications.According to an embodiment of the present disclosure, for example, it may be suggested that the priority order of the logical channel of the AI / ML model training and inference data demand report MAC CE (or AI / ML data collection MAC CE) be lower than the priority of the data from any logical channel, except data from UL-CCCH.

[0277] For example, traffic prediction information based on AI / ML model training, model management, and model inference

[0278] For example, when a terminal performs AI / ML model training and / or model inference functions, the terminal may transmit traffic prediction information based on AI / ML model training, model management, and inference to a base station or core network entity. For example, the base station may also allocate BWP (e.g., wide BWP or narrow BWP) or bandwidth resources (e.g., wide bandwidth or narrow bandwidth) to the terminal based on the traffic prediction information reported by the terminal. For example, or the base station may switch a BWP (e.g., wide BWP or narrow BWP) or bandwidth resource (e.g., wide bandwidth or narrow bandwidth) to another BWP (e.g., wide BWP or narrow BWP) or bandwidth resource (e.g., wide bandwidth or narrow bandwidth) based on traffic prediction information reported by the terminal.

[0279] For example, AI / ML model training, model management, and model-based traffic prediction information may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when traffic prediction information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this AI / ML-based traffic prediction report MAC CE be higher than the priority of data from any logical channel, except data from UL-CCCH, and lower than the priority of MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channels of this AI / ML-based traffic prediction report MAC CE be applied with a lower priority than the data from Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0280] For example, information on the data size required for communication operations based on AI / ML model training, model management, and model inference (e.g., the data size processed or to be processed through AI / ML model training, model management, and model inference; data transmission from the terminal to the base station based on this size may be required).

[0281] For example, when performing AI / ML model training, model management, and model inference at a terminal, data processed or to be processed through AI / ML model training, model management, and model inference may need to be transmitted to a base station or core network entity (e.g., a management entity for AI / ML support). For example, the terminal may also transmit size information regarding the terminal's AI / ML model training and model inference processing data to the base station so that the base station can allocate BWP and / or bandwidth suitable for the transmission of such data (for example, if the reported data size is large, the base station may reallocate the bandwidth part to a wide bandwidth part suitable for large data or allocate wide bandwidth resources).

[0282] For example, data size information required for AI / ML model training, model management, and model inference-based communication operations may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when data size information required for AI / ML model training, model management, and model inference-based communication operations is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this “data size information required for AI / ML model training, model management, and model inference-based communication operations” report MAC CE be higher in priority than data from any logical channel, except data from UL-CCCH, and lower in priority than MAC CE for other Uu communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channels of the “data size information required for AI / ML model training, model management and model inference-based communication operations” report MAC CE be applied with a lower priority than the data of Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0283] For example, information on the bandwidth (e.g., BWP or bandwidth) required for communication operations based on AI / ML model training, model management, and model inference (or AI / ML data collection) (e.g., transmission of training data, transmission of monitoring data, transmission of inference data or inference output, etc.).

[0284] For example, a terminal may transmit information regarding bandwidth (e.g., BWP or bandwidth) required for communication operations based on AI / ML model training, model management, and model inference (or AI / ML data collection) to a base station (e.g., 1. transmission of collected raw data used for AI / ML model training, model management, and inference, e.g., transmission of sensing measurement data, transmission of channel measurement data, transmission of non-3GPP data (e.g., video) 2. transmission of AI / ML model inference data or transmission of AI / ML model inference output data, etc.). For example, the base station may set or allocate BWP and bandwidth for AI / ML-based communication operations to the terminal by referring to the bandwidth information requested by the terminal.

[0285] For example, bandwidth information (e.g., BWP or bandwidth) may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when bandwidth request information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this required bandwidth report MAC CE be higher than the priority of data from any logical channel, except data from UL-CCCH, and lower than the priority of MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channels of this “required bandwidth report” MAC CE be applied with a lower priority than the data of Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0286] - - For example, trained / updated model size

[0287] For example, a trained, validated, and tested AI / ML model may be delivered to a model storage function, or an updated version of the model may be delivered to a model storage function. Therefore, for example, a terminal may need to be allocated an appropriate BWP or bandwidth before transmitting the trained / updated model to a base station and a core network entity (e.g., a network entity with a model storage function implemented). Therefore, for example, the terminal may transmit information regarding the size of the trained / updated model to the base station so that the base station and the network may perform switching (or allocation) to the BWP required for model size transmission or allocate the bandwidth required for model size transmission.

[0288] For example, a terminal may transmit information regarding bandwidth (e.g., BWP or bandwidth) required for communication operations based on AI / ML model training, model management, and model inference (or AI / ML data collection) to a base station (e.g., 1. transmission of collected raw data used for AI / ML model training, model management, and inference, e.g., transmission of sensing measurement data, transmission of channel measurement data, transmission of non-3GPP data (e.g., video) 2. transmission of AI / ML model inference data, etc.). For example, the base station may set or allocate BWP and bandwidth for AI / ML-based communication operations to the terminal by referring to the bandwidth information requested by the terminal.

[0289] For example, bandwidth information (e.g., BWP or bandwidth) may also be transmitted to the base station in the form of a MAC CE format or a dedicated RRC message (e.g., UE assistance information). For example, when bandwidth request information is transmitted via MAC CE, it may be proposed that the priority order of the logical channel of this required bandwidth report MAC CE be higher than the priority of data from any logical channel, except data from UL-CCCH, and lower than the priority of MAC CE for other UU communications. According to an embodiment of the present disclosure, for example, it may be proposed that the priority order of the logical channels of this “required bandwidth report” MAC CE be applied with a lower priority than the data of Uu communication (e.g., data from any logical channel, except data from UL-CCCH).

[0290] For example, an AI / ML-based sensing operation support method can be proposed at ISAC.

[0291] For example, to increase the reliability of sensing results, information on AI / ML-based model training and AI / ML-based model inference can be utilized.

[0292] In the present disclosure, for example, an AI / ML-based sensing data collection and collected sensing data reporting method at ISAC may be proposed as follows.

[0293] - For example, a sensing data collection procedure for extracting AI / ML-based sensing output

[0294] For example, sensing information collected based on the monitoring of a sensing signal (e.g., a sensing reference signal) can be used as an input for model training (e.g., AI / ML model training) and model inference (e.g., AI / ML model inference) by an entity supporting AI / ML operations (e.g., a UE, TRP, base station, or sensing function).

[0295] - - - For example, 1) Data collection for device-side model training and model inference (e.g., performing AI / ML model training and AI / ML model inference procedures on the sensing device)

[0296] - - - For example, when AI / ML model training and model inference operations for supporting AI / ML-based sensing services are performed on a sensing device (e.g., a sensing TX device and / or a sensing RX device), the triggering operation for the AI / ML model training and AI / ML model inference of the sensing device may be initiated or stopped as follows.

[0297] For example, a sensing function can trigger and initiate data collection for AI / ML-based model training and model inference in a sensing device when the following conditions are satisfied.

[0298] For example, when a sensing service (e.g., tracking / detection / localization information of an OBJ) is requested from a service provider, the sensing function can trigger and initiate the collection of sensing data by a sensing device to support AI / ML-based sensing services. The sensing device can perform model training and model inference for AI / ML based on the collected data. For example, the inferred sensing results can be reported to the sensing function.

[0299] For example, a sensing function may trigger and initiate the collection of sensing data from a sensing device to support AI / ML-based sensing services when the reliability (e.g., sensing data accuracy) of a non-AI / ML-based sensing output (e.g., sensing result) is below a QoS requirement threshold. For example, the sensing device may perform model training and model inference for AI / ML based on the collected data. For example, the inferred sensing result may be reported to the sensing function.

[0300] For example, a sensing function may trigger and initiate the collection of sensing data from a sensing device to support AI / ML-based sensing services when the sensing QoS requirements of a non-AI / ML-based sensing output (e.g., a sensing result) are below (or above) a threshold. For example, the sensing device may perform model training and model inference for AI / ML based on the collected data. For example, the inferred sensing result may be reported to the sensing function.

[0301] - - - - - - For example, sensing QoS requirements

[0302] For example, sensing QoS for detection, localization, and tracking**

[0303] For example, Detection QoS: Detection probability, False alarm probability

[0304] For example, localization QoS: localization of the static objects. For example, QoS parameter of localization (time delay, angle of arrival)

[0305] For example, Tracking QoS: Tracking the state variation (range, angle, velocity, etc.) of a moving target (e.g., vehicle or drone)

[0306] - - - - For example, a sensing device (e.g., a sensing TX device or a sensing RX device) can initiate a data collection process for AI / ML-based model training and model inference on its own when the following conditions are satisfied.

[0307] - - - - - For example, if an AI / ML-based sensing support operation is activated, and if setting information for a sensing reference signal (e.g., reference signal transmission start time, reference signal transmission period, transmission resource, reference signal type, etc.) is received from a base station or a sensing function.

[0308] For example, if an AI / ML-based sensing support operation is activated, the sensing device can initiate a data collection process based on the configuration information (e.g., data collection interval, data collection repetition cycle, etc.) if it has received configuration information for the AI / ML-based sensing support operation.

[0309] For example, the sensing function can stop collecting data for AI / ML-based model training and model inference in the sensing device when the following conditions are satisfied.

[0310] - - - - - For example, when the remaining battery of a sensing device based on auxiliary information (e.g., remaining battery information) transmitted by a sensing device (e.g., a sensing TX device or a sensing RX device) is below a threshold

[0311] For example, when sensing data collection is no longer required (for example, when the sensing function determines that data collection for the sensing service is complete)

[0312] For example, the sensing device may stop the data collection process upon receiving an explicit stopping indication from the sensing function.

[0313] For example, a sensing function can transmit a sensing data collection operation configuration for model training and model inference to a sensing device:

[0314] For example, a sensing function can transmit information to the sensing device regarding a setting that allows the sensing device to directly determine and initiate (or start) an AI-based sensing operation (e.g., performance monitoring, data collection) (e.g., allowing the sensing device to perform an AI / ML-based sensing operation, not allowing the sensing device to perform an AI / ML-based sensing operation).

[0315] For example, a configuration (for example, a sensing function can transmit to the sensing device whether to allow the initiation of the sensing device's AI-based sensing operation based on auxiliary information transmitted by the sensing device.)

[0316] - - - - - - - For example, allow a sensing device to perform AI / ML-based sensing operations (e.g., AI / ML model training and model inference operations for generating sensing results)

[0317] For example, the sensing device is not allowed to perform AI / ML-based sensing operations (e.g., AI / ML model training and model inference operations for generating sensing results).

[0318] - - - - For example, auxiliary information that a sensing device transmits to a sensing function

[0319] - - - - - For example, AI / ML aided sensing function (e.g., extraction of sensing results based on AI / ML model training and AI / ML model inference.) capability (e.g., AI / ML aided sensing function capability: supported or not supported)

[0320] - - - - - For example, the remaining battery amount of the sensing device

[0321] - - - - - For example, the number of TRPs transmitting downlink sensing reference signals: For example, if there are many sensing reference signals to be received and collected, the information can be passed to the sensing function as auxiliary information so that the AI / ML aided sensing function can be triggered.

[0322] - - - - - For example, TRP area environmental information (whether LOS is guaranteed, number of scatters, wireless channel quality status, etc.)

[0323] For example, target sensing area information (e.g., TSA absolute / relative location information, number of TSA nearby sensing TX devices (e.g., TRP), number of TSA nearby sensing RX devices)

[0324] - - - - - For example, mobility information

[0325] For example, movement information of a sensing Tx device, a sensing RX device, a target object, or a target sensing area (e.g., direction of movement, speed of movement, etc.)

[0326] - - - - - For example, (transmitted, e.g., when supporting AI / ML-aided sensing operations) Buffer capability for collected data buffering: Maximum buffer size allowed for data collection as input for AI / ML model training and AI / ML model inference.

[0327] For example, auxiliary information that a sensing device wants to receive from a sensing function or network, or requests from a sensing function or network.

[0328] For example, a sensing device (e.g., a sensing reference signal RX device) can request some specific assistance data that will have impact on model training and model inference:

[0329] - - - - - - For example, the number of sensing TX devices that UE wants to receive the sensing-RS.

[0330] - - - - - - For example, the area of ​​sensing TX devices that UE wants to receive sensing-RS

[0331] For example, the “area of ​​target object” or “target sensing area (TSA)” that sensing device want to receive reflected sensing signal.

[0332] - - - For example, 2) data collection for network (e.g., sensing function, base station, or TRP)-side model training and model inference (e.g., model training and model inference procedures can be performed on network entities)

[0333] For example, when AI / ML model training and inference operations for supporting AI / ML-based sensing services are performed by a network entity (e.g., a sensing function, a base station, or a TRP), the triggering operation for the sensing data collection for the AI / ML model training and model inference of the network entity (e.g., the collection of sensing data is performed by a sensing device, and the network entity that receives the collected data from the sensing device may perform the model training and model inference procedures) may be initiated or stopped as follows.

[0334] For example, the condition proposed in 1) of the present disclosure (e.g., the procedure for initiating and stopping a data collection trigger for training and inference of a sensing device-side model) can be applied in the same way to the operation of 2) so that the sensing function can instruct the initiation / stopping of a data collection trigger for AI / ML model training and AI / ML model inference.

[0335] For example, a network can request specific assistance data that will have impact on model training or model inference from the sensing device.

[0336] - - - - - For example, information for checking the validity of sensing data collection

[0337] - - - - - - For example, time information of collected sensing data: Provides the start and end times of collection to determine the validity of the sensing data.

[0338] - - - - - For example, UE remaining battery information: Auxiliary information to trigger or stop AI-based performance monitoring / data collection

[0339] For example, the purpose is to prevent AI-based actions from being triggered when the UE's remaining battery is below a threshold.

[0340] - - - For example, 3) Reporting behavior and reporting resource allocation behavior of data collected for AI / ML model training and AI / ML model inference

[0341] - - - - For example, report message type

[0342] For example, collected data may be transmitted via MAC CE or RRC messages from a sensing device to a base station, from a sensing RX device to a base station (or TRP), or from a sensing RX device to a sensing TX device. For example, the LCP priority order of a message (e.g., MAC CE or RRC message) for transmitting collected data for AI / ML model training or AI / ML model inference may be defined to have the same priority order as a measurement report message for a communication service, or to have a priority order less than or equal to a measurement report message for a communication service, or to have a priority order greater than a measurement report message for a communication service.

[0343] - - - - - For example, a report via MAC CE

[0344] - - - - - For example, a report via an RRC message

[0345] - - - - For example, allocation of transmission resources for a report of collected data

[0346] - - - - - For example, configured grant-based resource allocation

[0347] For example, a sensing function can set a collection cycle (and collection time) for AI / ML model training and AI / ML model inference in a sensing device, so that the sensing device performs the data collection procedure for AI / ML model training and AI / ML model inference at each cycle (e.g., for a set time).

[0348] For example, a sensing function or base station can set a configured grant resource that is aligned with the data collection cycle to the sensing device.

[0349] For example, a sensing device may report collected data at every configured grant period (e.g., Sensing RX device → Base Station → Sensing Function or Sensing RX device → Sensing TX device → Sensing Function or Sensing RX device → Sensing Function). For example, at this time, resources within the configured grant period may be restricted so that they are allowed to be used only for the transmission of collected data within the configured grant period (e.g., equal to the collection period). For example, a base station, a sensing function, or a sensing TX device can also trigger the transmission of collected data from a sensing RX device by activating the use of a configured grant resource (e.g., via activation MAC CE).

[0350] For example, BSR-based resource allocation

[0351] - - - - - - For example, logical channel group (LCG), buffer size, maximum buffer limit (e.g., maximum buffer size limit for buffering or storing collected data from sensing devices for AI / ML model training or AI / ML model inference)

[0352] For example, by reporting the maximum buffer limitation of the sensing device, the network (e.g., base station or sensing function) can use this as auxiliary information on how to efficiently use all available resources (e.g., communication + sensing) for the sensing service.

[0353] For example, a maximum buffer limitation may be transmitted to a base station or a sensing function during capability information exchange, rather than to a BSR.

[0354] - - - - - For example, allocation of resources for data transmission based on scheduling requests (SR).

[0355] For example, regardless of the size of the collected data, the size of the collected data transmission resource that can be allocated at once can be fixed and mapped to a dedicated SR for the allocation of collected data transmission resources. For example, a base station (or TRP) can receive a dedicated SR for the transmission of collected data for AI / ML model training or AI / ML model inference and allocate a fixed amount of resources to the device corresponding to the site mapped to that SR.

[0356] - - - - For example, start condition for reporting the “collected data”

[0357] For example, a report every configured grant period dedicated to collected data.

[0358] For example, when a configured grant activation MAC CE is received for data collection only, report at every configured grant cycle until a deactivation MAC CE is received.

[0359] - - - - For example, stopping condition for reporting the “collected data”

[0360] - - - - - For example, upon receiving an explicit indication from a sensing function.

[0361] - - - - - For example, when the remaining battery capacity is below the threshold.

[0362] A combination of embodiments of the present disclosure may operate in conjunction with each other.

[0363] Various embodiments of the present disclosure may be applied differently depending on the link type (DL, UL, SL) and / or the data type (SIB, group cast, unicast) and / or the search space type (CSS (common search space), USS (UE-specific search space)) where the scheduling PDCCH is detected and / or the base station node type and / or altitude and / or whether there is a power constraint. For example, a combination of various embodiments of the present disclosure may be applied only when involved in SIB transmission.

[0364] For example, in the present disclosure, the machine learning model may be an AI / ML model.

[0365] For example, in the present disclosure, a base station or network may be a TRP and / or an NB and / or an AMF and / or a (system) core. For example, in the present disclosure, an NB may be an AMF and / or a (system) core. For example, in the present disclosure, a system core may be an AMF and / or a (system) core.

[0366] For example, in the present disclosure, a sensing signal may be interpreted as having the same meaning as a sensing reference signal.

[0367] For example, in the present disclosure, sensing data may be interpreted as having the same meaning as sensing measurement data or sensing measurement report.

[0368] For example, the embodiments of the present disclosure may be extended to all of the above six sensing scenarios. For example, the embodiments of the present disclosure may be applicable to all of the above six sensing scenarios.

[0369] For example, the methods proposed in this disclosure can be applied to both 3GPP sensing data and non-3GPP sensing data.

[0370] For example, in the present disclosure, sensing data may be data derived by a sensing radio measurement entity based on radio signals (e.g., reflected, refracted, diffracted) affected by an object or environment of interest for the purpose of sensing. For example, this data may be raw measurements and may optionally be further processed within the sensing radio measurement entity. For example, the sensing data may include at least one of 3GPP sensing data or non-3GPP sensing data.

[0371] For example, in the present disclosure, 3GPP sensing data is data obtained from 3GPP radio signals that have been affected (e.g., reflected, refracted, diffracted) by an object or environment of interest for the purpose of sensing, and may optionally be processed within a 5G system.

[0372] For example, in the present disclosure, non-3GPP sensing data may be data provided by a non-3GPP sensor (e.g., video, LiDAR, sonar) regarding an object or environment of interest for the purpose of sensing.

[0373] For example, in the present disclosure, 5G / 6G radio sensing may be a 5GS / 6GS function that provides a function to acquire information about the characteristics of an environment and / or objects within the environment (e.g., shape, size, orientation, speed, location, distance, relative movement between objects, etc.) using NR radio frequency signals, and may, in some cases, be extended by information generated through a previously defined function in the EPC and / or E-UTRAN.

[0374] For example, in the present disclosure, sensing auxiliary information may be information provided to a 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. For example, examples of sensing auxiliary information may include map information, location information, a UE identifier (ID) attached to or located near a sensing target, UE location information, UE velocity information, etc.

[0375] 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 the sensing results, and may provide 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, location information, time of capture, UE location, and ID. This context information may be required in scenarios where the sensing results need to be combined with data from other sources outside of 5GS.

[0376] 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.

[0377] For example, in the present disclosure, a sensing receiver may be an entity that receives a sensing signal used by a sensing service in operation. The sensing receiver may be a RAN node or part of a UE. The sensing receiver may be located in the same entity as the sensing transmitter or in a different entity.

[0378] For example, in the present disclosure, the sensing result may be processed 3GPP sensing data requested by a service consumer.

[0379] 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 NR radio frequency signals and, in some cases, may be extended to information generated from existing functions of the EPC and / or E-UTRAN.

[0380] For example, a sensing transmitter may be an entity that transmits a sensing signal used by a sensing service in an operation. A sensing transmitter may be part of a RAN node or a UE. A sensing transmitter may be located in the same entity as a sensing receiver or in a different entity.

[0381] For example, the target sensing service area may be an orthogonal coordinate location area that satisfies a specific sensing service quality and is to be sensed by deriving the characteristics of the environment and / or objects within the environment from 3GPP radio signals that have been affected (e.g., reflected, refracted, diffracted). This may include both indoor and outdoor environments.

[0382] For example, the present disclosure may be applied to base stations (e.g., TRP) and / or terminal monostatics. For example, the present disclosure may also be applied to base station-base station (e.g., TRP-TRP), base station-UE (e.g., TRP-UE), UE-base station (e.g., UE-TRP), and / or UE-UE bistatics.

[0383] For example, in the present disclosure, "specific threshold" may mean a threshold that is predefined or (pre-)set by an upper layer (including the application layer) of a network, base station, or terminal. For example, in the present disclosure, "specific set value" may mean a value that is predefined or (pre-)set by an upper layer (including the application layer) of a network, base station, or terminal. For example, in the present disclosure, "set by the network / base station" may mean an action in which a base station sets to a UE (pre-) through upper layer RRC signaling, sets / signals to a UE through MAC CE, or signals to a UE through DCI.

[0384] For example, in the present disclosure, a message may be interpreted as being replaced by at least one of a control message, a data message, a signal, a data signal, and / or a control signal.

[0385] For example, in this disclosure, various names are exemplary and may be replaced or considered as other names performing the same or similar functions based on the content described in each step (regardless of the name).

[0386] For example, in the present disclosure, the bandwidth part (BWP) may be replaced with a bandwidth setting set or a wireless resource set, etc.

[0387] For example, in the present disclosure, the wireless resource profile exemplified may be applied as a BWP (bandwidth part), a bandwidth setting set, a wireless resource set, etc.

[0388] For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically to the resource pool (or differently or independently). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically to the congestion level (or differently or independently). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically to the service priority (or differently or independently). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically to the service type (or differently or independently). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically to QoS requirements (e.g., latency, reliability) (or differently or independently). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically (or differently or independently) to PQI (5QI (5G QoS identifier) ​​for PC5). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically (or differently or independently) to traffic types (e.g., periodic generation or non-periodic generation). For example, the applicability of (some) proposed methods / rules of the present disclosure and / or related parameters (e.g., thresholds) may be set specifically (or differently or independently) to SL transmission resource allocation modes (e.g., Mode 1 or Mode 2).For example, whether the (some) proposed methods / rules of the present disclosure apply and / or related parameters (e.g., thresholds) may be specifically (or differently or independently) set to 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 support sidelink DRX operation).

[0389] For example, the applicability of the proposed rules of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set depending on whether PUCCH setting is supported (e.g., when a PUCCH resource is set or when a PUCCH resource is not set). For example, the applicability of the proposed rules of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set for a resource pool (e.g., a resource pool where PSFCH is set or a resource pool where PSFCH is not set). For example, the applicability of the proposed rules of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set for the type of service / packet. For example, the applicability of the proposed rules of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set for the priority of the service / packet. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be set specifically (or differently or independently) to a QoS profile or QoS requirements (e.g., URLLC / EMBB traffic, reliability, latency). For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be set specifically (or differently or independently) to a PQI. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be set specifically (or differently or independently) to a PFI. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be set specifically (or differently or independently) to a cast type (e.g., unicast, groupcast, broadcast). For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be set specifically (or differently or independently) to a (resource pool) congestion level (e.g., CBR).For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting value may be set specifically (or differently or independently) to an SL HARQ feedback method (e.g., NACK-only feedback, ACK / NACK feedback). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting value may be set specifically (or differently or independently) to HARQ Feedback Enabled MAC PDU transmission. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting value may be set specifically (or differently or independently) to HARQ Feedback Disabled MAC PDU transmission. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting value may be set specifically (or differently or independently) depending on whether a PUCCH-based SL HARQ feedback reporting operation is enabled. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set depending on whether pre-emption or pre-emption-based resource reselection is performed. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set depending on whether re-evaluation or re-evaluation-based resource reselection is performed. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set to the (L2 or L1) (source and / or destination) identifier. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting values ​​may be specifically (or differently or independently) set to the (L2 or L1) (combination of source ID and destination ID) identifier.For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting value may be set specifically (or differently or independently) to the identifier (L2 or L1) (combination of the pair of source ID and destination ID and cast type). For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting value may be set specifically (or differently or independently) to the direction of the pair of source layer ID and destination layer ID. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting value may be set specifically (or differently or independently) to the PC5 RRC connection / link. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting value may be set specifically (or differently or independently) depending on whether SL DRX is performed. For example, the applicability of the proposal rule of the present disclosure and / or the related parameter setting value may be set specifically (or differently or independently) depending on whether SL DRX is supported. For example, whether the proposed rules of the present disclosure apply and / or the related parameter setting values ​​may be set specifically (or differently or independently) to an SL mode type (e.g., resource allocation mode 1 or resource allocation mode 2). For example, whether the proposed rules of the present disclosure apply and / or the related parameter setting values ​​may be set specifically (or differently or independently) to cases where (non)periodic resource reservation is performed. For example, whether the proposed rules of the present disclosure apply and / or the related parameter setting values ​​may be set specifically (or differently or independently) to 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 support sidelink DRX operation).

[0390] The applicability of the proposals and proposal rules of the present disclosure (and / or related parameter setting values) may also apply to mmWave sidelink operations.

[0391] For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the service type (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the priority (LCH or service) (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to QoS requirements (e.g., latency, reliability, minimum communication range) (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the PQI parameter (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the SL HARQ feedback ENABLED LCH / MAC PDU (transmission) (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to SL HARQ feedback DISABLED LCH / MAC PDU (transmission). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to CBR measurement values ​​of the resource pool. For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to SL cast type (e.g., unicast, groupcast, broadcast).For example, the application status of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to SL GroupCast HARQ feedback options (e.g., NACK only feedback, ACK / NACK feedback, TX-RX distance-based NACK only feedback). For example, the application status of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to SL Mode 1 CG type (e.g., SL CG type 1 or SL CG type 2). For example, the application status of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to SL Mode type (e.g., Mode 1 or Mode 2). For example, the application status of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to resource pool. For example, the parameter values ​​regarding the applicability of the above rule and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) depending on whether the PSFCH resource is a resource pool where it is configured. For example, the parameter values ​​regarding the applicability of the above rule and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) depending on the source (L2) ID. For example, the parameter values ​​regarding the applicability of the above rule and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) depending on the destination (L2) ID. For example, the parameter values ​​regarding the applicability of the above rule and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) depending on the PC5 RRC connection link.For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the SL link (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the connection status (e.g., RRC CONNECTED status, IDLE status, INACTIVE status) (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the SL HARQ process (ID) (or differently or independently). For example, the applicability of the above rule and / or parameter values ​​related to the proposed method / rule of the present disclosure may be set / allowed specifically to the SL DRX operation (of the TX UE or RX UE) (or differently or independently). For example, the parameter values ​​regarding whether the above rule applies and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to the power saving (TX or RX) UE. For example, the parameter values ​​regarding whether the above rule applies and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to the case where PSFCH TX and PSFCH RX overlap (and / or multiple PSFCH TXs exceeding the UE's capability) (and / or where PSFCH TX (and / or PSFCH RX) are omitted) from the perspective of a specific UE. For example, the parameter values ​​regarding whether the above rule applies and / or the proposed method / rule of the present disclosure may be set / allowed specifically (or differently or independently) to the case where the RX UE actually (successfully) receives a PSCCH (and / or PSSCH) (re)transmission from the TX UE.

[0392] For example, the setting (or designation) wording in the present disclosure may be interpreted in an extended manner, such as a form in which a base station informs 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 informs another terminal through a predefined (physical layer or upper layer) channel / signal (e.g., SL MAC CE, PC5 RRC)).

[0393] For example, the PSFCH wording in the present disclosure may 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)). Additionally, the proposed methods of the present disclosure may be combined with each other and extended (in a new form).

[0394] For example, in the present disclosure, a specific threshold value may refer to a threshold value that is predefined or set (in advance) by an upper layer (including the application layer) of a network, base station, or terminal. For example, in the present disclosure, a specific setting value may refer to a value that is predefined or set (in advance) by an upper layer (including the application layer) of a network, base station, or terminal. For example, an operation set by a network / base station may refer to an operation in which the base station sets (in advance) to the UE through upper layer RRC signaling, sets / signals to the UE through MAC CE, or signals to the UE through DCI.

[0395] The operation of the present disclosure can be applied to all side-link unicast / group cast / broadcast operations.

[0396] In an embodiment of the present disclosure, the message may be interpreted as being replaced with a control message or a data message or a signal or a data signal or a control signal.

[0397] In an embodiment of the present disclosure, a beam management operation may be interpreted as being replaced by 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 a reference signal resource or measurement of a reference signal resource reporting operation or beam reporting or spatial filter reporting, etc.

[0398] In an embodiment of the present disclosure, the beam may be interpreted by replacing it with an RS or an RS resource or a spatial filter resource.

[0399] In an embodiment of the present disclosure, RS can be interpreted as being replaced by an RS resource or a spatial filter resource.

[0400] In an embodiment of the present disclosure, the transmission terminal may be interpreted as being replaced with a terminal that transmits a beam, a terminal that transmits a beam RS, or a terminal that transmits a beam RS resource, etc.

[0401] In an embodiment of the present disclosure, the receiving terminal may be interpreted as being replaced with a terminal receiving a beam, a terminal receiving a beam RS, or a terminal receiving a beam RS resource.

[0402] 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 a reference signal (RS) associated with the transmission beam and resource information of a reference signal (RS) associated with the reception beam.

[0403] In an embodiment of the present disclosure, a DCR (direct communication request) and / or DCA (direct communication accept) message may be interpreted as being replaced by a PC5-S DCR and / or PC5-S DCA message, etc.

[0404] 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 by beam-related information, beam direction, spatial domain transmission or reception filter, etc.

[0405] In an embodiment of the present disclosure, the beam may be interpreted as being replaced by a transmitting beam or a receiving beam or a spatial filter or a spatial transmission (TX) filter or a spatial area transmission (TX) filter or a spatial reception (RX) filter or a spatial area reception (RX) filter.

[0406] In an embodiment of the present disclosure, the transmit / transmit beam may be interpreted as being replaced by a spatial transmission (TX) filter or a spatial area transmission (TX) filter.

[0407] In an embodiment of the present disclosure, the receiving beam may be interpreted as being replaced by a spatial receiving (RX) filter or a spatial area receiving (RX) filter.

[0408] In an embodiment of the present disclosure, the fact that the spatial setting information (or beam information) for transmission is identical may mean that the spatial area TX filter of the terminal is identical for two different transmission signals. In an embodiment of the present disclosure, the fact that the spatial setting information (or beam information) for reception is identical may mean that two different reception signals are in a QCL 'TypeD' relationship and / or have a relationship using the same spatial RX parameter.

[0409] 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) that is not a radar signal.

[0410] 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 a source layer 2 ID and a destination layer 2 ID.

[0411] FIG. 13 illustrates a procedure performed by a first device according to one embodiment of the present disclosure. The embodiment of FIG. 13 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, suggestions, methods, and / or operations of said embodiments may be omitted.

[0412] Referring to FIG. 13, in step S1310, the first device may obtain information related to the sensing resolution. In step S1320, the first device may include the information related to the sensing resolution in auxiliary information. In step S1330, the first device may transmit the auxiliary information containing the information related to the sensing resolution to the second device.

[0413] For example, the above auxiliary information may be UE (user equipment) auxiliary information. For example, the above UE auxiliary information may be transmitted as a dedicated RRC (radio resource control) message.

[0414] For example, the information related to the sensing resolution may be sensing resolution requirement information. For example, the sensing resolution requirement information may include at least one of information related to high resolution, information related to medium resolution, or information related to low resolution.

[0415] For example, the above auxiliary information may include information related to a target detection range. For example, the information related to the target detection range may include at least one of information related to long range detection, information related to medium range detection, or information related to short range detection.

[0416] For example, the above auxiliary information may include information related to movement speed. For example, the information related to movement speed may be at least one of information related to the movement speed of a terminal, information related to the movement speed of a target sensing area, or information related to the movement speed of a target object. For example, the information related to movement speed may include at least one of information related to high-speed movement speed, information related to medium-speed movement speed, or information related to low-speed movement speed.

[0417] For example, the above auxiliary information may include information related to sensing traffic patterns.

[0418] For example, the above auxiliary information may include information related to the data collection data requirement.

[0419] For example, the above auxiliary information may include at least one of information related to the training data requirements of an AI / ML (artificial intelligence / machine learning) model, information related to the management data requirements of an AI / ML model, or information related to the inference data requirements of an AI / ML model.

[0420] For example, the above auxiliary information may include traffic prediction information based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0421] For example, the above auxiliary information may include information related to the data size required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0422] For example, the above auxiliary information may include information related to bandwidth required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0423] For example, the above auxiliary information may include information related to the size of a trained AI / ML model or information related to the size of an updated AI / ML model.

[0424] For example, the first device may be a sensing transmission device or a sensing reception device. For example, the second device may be a base station or a sensing function.

[0425] The proposed method above may be applied to a device according to various embodiments of the present disclosure. For example, a processor (102) of a first device (100) may acquire information related to a sensing resolution (for example, the processor (102) of the first device (100) may control a transceiver (106) to acquire information related to a sensing resolution). For example, the processor (102) of the first device (100) may include the information related to the sensing resolution in auxiliary information (for example, the processor (102) of the first device (100) may control a transceiver (106) to include the information related to the sensing resolution in auxiliary information). For example, the processor (102) of the first device (100) may transmit a sensing rejection message based on the sensing notification (for example, the processor (102) of the first device (100) may control the transceiver (106) to transmit a sensing rejection message based on the sensing notification).

[0426] 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 connected to the at least one processor and storing instructions. For example, based on the instructions executed by the at least one processor, the first device may: acquire information related to a sensing resolution; include said information related to the sensing resolution in auxiliary information; and transmit said auxiliary information including said information related to the sensing resolution to a second device.

[0427] For example, the above auxiliary information may be UE (user equipment) auxiliary information. For example, the above UE auxiliary information may be transmitted as a dedicated RRC (radio resource control) message.

[0428] For example, the information related to the sensing resolution may be sensing resolution requirement information. For example, the sensing resolution requirement information may include at least one of information related to high resolution, information related to medium resolution, or information related to low resolution.

[0429] For example, the above auxiliary information may include information related to a target detection range. For example, the information related to the target detection range may include at least one of information related to long range detection, information related to medium range detection, or information related to short range detection.

[0430] For example, the above auxiliary information may include information related to movement speed. For example, the information related to movement speed may be at least one of information related to the movement speed of a terminal, information related to the movement speed of a target sensing area, or information related to the movement speed of a target object. For example, the information related to movement speed may include at least one of information related to high-speed movement speed, information related to medium-speed movement speed, or information related to low-speed movement speed.

[0431] For example, the above auxiliary information may include information related to sensing traffic patterns.

[0432] For example, the above auxiliary information may include information related to the data collection data requirement.

[0433] For example, the above auxiliary information may include at least one of information related to the training data requirements of an AI / ML (artificial intelligence / machine learning) model, information related to the management data requirements of an AI / ML model, or information related to the inference data requirements of an AI / ML model.

[0434] For example, the above auxiliary information may include traffic prediction information based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0435] For example, the above auxiliary information may include information related to the data size required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0436] For example, the above auxiliary information may include information related to bandwidth required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0437] For example, the above auxiliary information may include information related to the size of a trained AI / ML model or information related to the size of an updated AI / ML model.

[0438] For example, the first device may be a sensing transmission device or a sensing reception device. For example, the second device may be a base station or a sensing function.

[0439] 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 connected to the at least one processor and storing instructions. For example, the instructions may cause the first device, based on execution by the at least one processor: to acquire information related to a sensing resolution; to include said information related to the sensing resolution in auxiliary information; and to transmit said auxiliary information including said information related to the sensing resolution to a second device.

[0440] According to one embodiment of the present disclosure, a non-transient computer-readable storage medium recording instructions may be provided. For example, when the instructions are executed, the first device may: acquire information related to a sensing resolution; include said information related to the sensing resolution in auxiliary information; and transmit said auxiliary information including said information related to the sensing resolution to a second device.

[0441] FIG. 14 illustrates a procedure performed by a second device 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, suggestions, methods, and / or operations of said embodiments may be omitted.

[0442] Referring to FIG. 14, in step S1410, the second device can establish a radio resource control (RRC) connection with the first device. In step S1420, based on the RRC connection, the second device can receive auxiliary information from the first device including information related to sensing resolution.

[0443] For example, the above auxiliary information may be UE (user equipment) auxiliary information. For example, the above UE auxiliary information may be transmitted as a dedicated RRC (radio resource control) message.

[0444] For example, the information related to the sensing resolution may be sensing resolution requirement information. For example, the sensing resolution requirement information may include at least one of information related to high resolution, information related to medium resolution, or information related to low resolution.

[0445] For example, the above auxiliary information may include information related to a target detection range. For example, the information related to the target detection range may include at least one of information related to long range detection, information related to medium range detection, or information related to short range detection.

[0446] For example, the above auxiliary information may include information related to movement speed. For example, the information related to movement speed may be at least one of information related to the movement speed of a terminal, information related to the movement speed of a target sensing area, or information related to the movement speed of a target object. For example, the information related to movement speed may include at least one of information related to high-speed movement speed, information related to medium-speed movement speed, or information related to low-speed movement speed.

[0447] For example, the above auxiliary information may include information related to sensing traffic patterns.

[0448] For example, the above auxiliary information may include information related to the data collection data requirement.

[0449] For example, the above auxiliary information may include at least one of information related to the training data requirements of an AI / ML (artificial intelligence / machine learning) model, information related to the management data requirements of an AI / ML model, or information related to the inference data requirements of an AI / ML model.

[0450] For example, the above auxiliary information may include traffic prediction information based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0451] For example, the above auxiliary information may include information related to the data size required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0452] For example, the above auxiliary information may include information related to bandwidth required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0453] For example, the above auxiliary information may include information related to the size of a trained AI / ML model or information related to the size of an updated AI / ML model.

[0454] For example, the first device may be a sensing transmission device or a sensing reception device. For example, the second device may be a base station or a sensing function.

[0455] The proposed method above may be applied to a device according to various embodiments of the present disclosure. For example, a processor (202) of a second device (200) may establish a radio resource control (RRC) connection with a first device (for example, the processor (202) of the second device (200) may control a transceiver (206) to establish a radio resource control (RRC) connection with the first device). For example, the processor (202) of the second device (200) may receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection (for example, the processor (202) of the second device (200) may control a transceiver (206) to receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection).

[0456] 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 connected to the at least one processor and storing instructions. For example, the instructions may cause the second device to: establish a radio resource control (RRC) connection with the first device based on execution by the at least one processor; and receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection.

[0457] For example, the above auxiliary information may be UE (user equipment) auxiliary information. For example, the above UE auxiliary information may be transmitted as a dedicated RRC (radio resource control) message.

[0458] For example, the information related to the sensing resolution may be sensing resolution requirement information. For example, the sensing resolution requirement information may include at least one of information related to high resolution, information related to medium resolution, or information related to low resolution.

[0459] For example, the above auxiliary information may include information related to a target detection range. For example, the information related to the target detection range may include at least one of information related to long range detection, information related to medium range detection, or information related to short range detection.

[0460] For example, the above auxiliary information may include information related to movement speed. For example, the information related to movement speed may be at least one of information related to the movement speed of a terminal, information related to the movement speed of a target sensing area, or information related to the movement speed of a target object. For example, the information related to movement speed may include at least one of information related to high-speed movement speed, information related to medium-speed movement speed, or information related to low-speed movement speed.

[0461] For example, the above auxiliary information may include information related to sensing traffic patterns.

[0462] For example, the above auxiliary information may include information related to the data collection data requirement.

[0463] For example, the above auxiliary information may include at least one of information related to the training data requirements of an AI / ML (artificial intelligence / machine learning) model, information related to the management data requirements of an AI / ML model, or information related to the inference data requirements of an AI / ML model.

[0464] For example, the above auxiliary information may include traffic prediction information based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0465] For example, the above auxiliary information may include information related to the data size required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0466] For example, the above auxiliary information may include information related to bandwidth required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

[0467] For example, the above auxiliary information may include information related to the size of a trained AI / ML model or information related to the size of an updated AI / ML model.

[0468] For example, the first device may be a sensing transmission device or a sensing reception device. For example, the second device may be a base station or a sensing function.

[0469] 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 connected to the at least one processor and storing instructions. For example, the instructions may cause the second device to: establish a radio resource control (RRC) connection with the first device based on execution by the at least one processor; and receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection.

[0470] According to one embodiment of the present disclosure, a non-transient computer-readable storage medium recording instructions may be provided. For example, when the instructions are executed, the second device may: establish a radio resource control (RRC) connection with the first device; and receive auxiliary information including information related to sensing resolution from the first device based on the RRC connection.

[0471] According to an embodiment of the present disclosure, by transmitting auxiliary information including information related to sensing resolution to a base station, the base station can efficiently allocate resources for sensing services and AI / ML-based communication based on said information.

[0472] Accordingly,

[0473] - It is possible to secure the necessary bandwidth and resources in advance, even during high-resolution sensing and large-capacity data transmission, and

[0474] - Resource management is possible considering the amount of data and bandwidth requirements necessary for AI / ML model training, management, and inference, and

[0475] - The accuracy, processing efficiency, and response speed (QoS and latency) of sensing and AI / ML services are improved.

[0476] As a result, according to the present disclosure, in a newly introduced sensing and AI / ML convergence service environment in an NR system, the efficiency of resource allocation, sensing performance, overall system operational stability, and resource utilization rate can be significantly improved.

[0477] Various embodiments of the present disclosure may be combined with one another. For example, various embodiments of the present disclosure may be combined with one another, and some descriptions, functions, procedures, suggestions, methods, and / or operations of the various embodiments may be omitted.

[0478] The present disclosure describes a 5G wireless communication system as an example. This can be similarly applied and used in 6G wireless communication systems, etc.

[0479] The proposed method above may be applied to the device described below. First, the processor (202) of the receiving terminal may set at least one partial bandwidth (e.g., BWP; bandwidth part). Then, the processor (202) of the receiving terminal may 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).

[0480] The following describes an apparatus to which various embodiments of the present disclosure may be applied.

[0481] The various descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed in this document, though not limited thereto, may be applied to various fields requiring wireless communication / connection (e.g., 5G, 6G, etc.) between devices.

[0482] Examples are provided in more detail below with reference to the drawings. In the following drawings and descriptions, the same reference numerals may represent the same or corresponding hardware blocks, software blocks, or function blocks unless otherwise described.

[0483] FIG. 15 shows a communication system (1) 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, suggestions, methods and / or operations of the embodiments may be omitted.

[0484] Referring to FIG. 15, 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 wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution), 6G) and may be referred to as a communication / wireless / 5G / 6G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Thing) device (100f), and an AI device / server (400). For example, the vehicle may include a vehicle equipped with wireless communication functions, an autonomous vehicle, a vehicle capable of performing inter-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., Advanced Air Mobility). The XR device includes 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, digital signage, a vehicle, a robot, etc. The portable device may include a smartphone, a smartpad, a wearable device (e.g., a smartwatch, smart glasses), a computer (e.g., a laptop, 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 be implemented as a wireless device, and a specific wireless device (200a) may operate as a base station / network node to other wireless devices.

[0485] Here, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present disclosure may include LTE, NR, and 6G, as well as NB-IoT (Narrowband Internet of Things) for low-power communication. In this case, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology and may be implemented according to standards such as LTE Cat NB1 and / or LTE Cat NB2, but is not limited to the names mentioned above. Additionally, or generally, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present disclosure may perform communication based on LTE-M technology. In this case, for example, LTE-M technology may be an example of LPWAN technology and may be referred to by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology may be implemented in 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 names mentioned above. Additionally or generally, wireless communication technology implemented in the wireless devices (100a to 100f) of the present disclosure may include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) for low-power communication, and is not limited to the names mentioned above. As an example, ZigBee technology can create personal area networks (PANs) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and may be referred to by various names.

[0486] Wireless devices (100a to 100f) can be connected to a network (300) through a base station (200). Artificial Intelligence (AI) technology may be applied to the wireless devices (100a to 100f), and wireless devices (100a to 100f) can be connected to an AI server (400) through 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, or a 6G network. Wireless devices (100a to 100f) may communicate with each other through the base station (200) / network (300), but they may 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). Also, IoT devices (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0487] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a~100f) / base station (200) and base station (200) / base station (200). Here, wireless communication / connection can be achieved through various wireless access technologies (e.g., 5G NR, 6G, etc.), such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and inter-base station communication (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 / from each other. For example, wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on the various proposals of the present disclosure, at least some of the following may be performed: 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.), resource allocation processes, etc.

[0488] FIG. 16 illustrates a wireless device 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, suggestions, methods, and / or operations of the embodiments may be omitted.

[0489] Referring to FIG. 16, the first wireless device (100) and the second wireless device (200) can transmit and receive wireless signals through various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (100), the second wireless device (200)} may correspond to {wireless device (100x), base station (200)} and / or {wireless device (100x), wireless device (100x)} of FIG. 15.

[0490] The first wireless device (100) includes one or more processors (102) and one or more memories (104), and may additionally include one or more transceivers (106) and / or one or more antennas (108). The processor (102) controls the memory (104) and / or transceivers (106) and may be configured to implement the descriptions, functions, procedures, proposals, methods and / or sequences of operation disclosed in this document. For example, the processor (102) may process information within the memory (104) to generate a first information / signal and then transmit a wireless signal containing the first information / signal through the transceiver (106). Additionally, the processor (102) may receive a wireless signal containing a second information / signal through the transceiver (106) and then store information obtained from the 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 store software code containing instructions for performing some or all of the processes controlled by the processor (102) or for performing the descriptions, functions, procedures, proposals, methods, and / or operation sequence diagrams disclosed in this document. Here, the processor (102) and the memory (104) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (106) may be connected to the processor (102) and may transmit and / or receive wireless signals through one or more antennas (108). The transceiver (106) may include a transmitter and / or receiver. The transceiver (106) may be combined with an RF (Radio Frequency) unit. In the present disclosure, a wireless device may refer to a communication modem / circuit / chip.

[0491] The second wireless device (200) includes one or more processors (202) and one or more memories (204), and may additionally include one or more transceivers (206) and / or one or more antennas (208). The processor (202) controls the memory (204) and / or transceivers (206) and may be configured to implement the descriptions, functions, procedures, proposals, methods and / or sequences of operation disclosed in this document. For example, the processor (202) may process information within the memory (204) to generate a third information / signal and then transmit a wireless signal containing the third information / signal through the transceiver (206). Additionally, the processor (202) may receive a wireless signal containing a fourth information / signal through the transceiver (206) and then store information obtained from the signal processing of the fourth information / signal in the memory (204). Memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, memory (204) may store software code containing instructions for performing some or all of the processes controlled by the processor (202) or for performing the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed in this document. Here, the processor (202) and memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). A transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals through one or more antennas (208). The transceiver (206) may include a transmitter and / or receiver. The transceiver (206) may be interchangeable with an RF unit. In this disclosure, a wireless device may refer to a communication modem / circuit / chip.

[0492] Hereinafter, 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 Service Data Units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation 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 flowcharts of operation disclosed in this document. One or more processors (102, 202) may generate a signal (e.g., baseband signal) containing a PDU, SDU, message, control information, data, or information according to the functions, procedures, proposals, and / or methods disclosed in this document and provide it to one or more transceivers (106, 206). One or more processors (102, 202) may receive a signal (e.g., baseband signal) from one or more transceivers (106, 206) and may obtain a PDU, SDU, message, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or flowcharts disclosed in this document.

[0493] One or more processors (102, 202) may be referred to as a controller, microcontroller, microprocessor, or 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 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. Firmware or software configured to perform the descriptions, functions, procedures, proposals, methods, and / or operation sequences disclosed in this document may be contained in one or more processors (102, 202) or stored in one or more memories (104, 204) and driven by one or more processors (102, 202). The descriptions, functions, procedures, proposals, methods, and / or operation sequences disclosed in this document may be implemented using firmware or software in the form of code, instructions, and / or sets of instructions.

[0494] One or more memories (104, 204) may be connected to one or more processors (102, 202) and may store various forms of data, signals, messages, information, programs, code, instructions, and / or commands. One or more memories (104, 204) may be composed of ROM, RAM, EPROM, flash memory, hard drive, registers, cache memory, computer read storage media, and / or combinations thereof. One or more memories (104, 204) may be located inside and / or outside of one or more processors (102, 202). Additionally, one or more memories (104, 204) may be connected to one or more processors (102, 202) through various technologies such as wired or wireless connections.

[0495] One or more transceivers (106, 206) may transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or operation flowcharts, etc., of this document to one or more other devices. One or more transceivers (106, 206) may receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or operation flowcharts, etc., disclosed in this document from one or more other devices. For example, one or more transceivers (106, 206) may be connected to one or more processors (102, 202) and may transmit and receive wireless signals. For example, one or more processors (102, 202) may 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 connected 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, etc., as described in the descriptions, functions, procedures, proposals, methods, and / or flowcharts of operation disclosed in this document through 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 the received wireless signal / channel, etc. from an RF band signal to a baseband signal in order to process the received user data, control information, wireless signal / channel, etc. using one or more processors (102, 202).One or more transceivers (106, 206) can convert user data, control information, wireless signals / channels, etc. processed using one or more processors (102, 202) from baseband signals to RF band signals. To this end, one or more transceivers (106, 206) may include (analog) oscillators and / or filters.

[0496] FIG. 17 illustrates a signal processing circuit for a transmission signal 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, suggestions, methods, and / or operations of the embodiments may be omitted.

[0497] Referring to FIG. 17, 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 operation / function of FIG. 17 may be performed in the processor (102, 202) and / or transceiver (106, 206) of FIG. 16. The hardware elements of FIG. 17 may be implemented in the processor (102, 202) and / or transceiver (106, 206) of FIG. 16. For example, blocks 1010 through 1060 may be implemented in the processor (102, 202) of FIG. 16. Additionally, blocks 1010 to 1050 may be implemented in the processor (102, 202) of FIG. 16, and block 1060 may be implemented in the transceiver (106, 206) of FIG. 16.

[0498] The codeword can be converted into a wireless signal through the signal processing circuit (1000) of FIG. 17. Here, the codeword is an encoded bit sequence of an information block. The information block may include a transmission block (e.g., UL-SCH transmission block, DL-SCH transmission block). The wireless signal can be transmitted through various physical channels (e.g., PUSCH, PDSCH).

[0499] Specifically, a codeword can be converted into a scrambled bit sequence by a scrambler (1010). The scrambled sequence used for scrambling is generated based on an initialization value, which may include ID information of a 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 an N*M precoding matrix W. Here, N is the number of antenna ports and M is the number of transmission layers. Here, the precoder (1040) can perform precoding after performing transform precoding (e.g., DFT transform) on the complex modulation symbols. Additionally, the precoder (1040) can perform precoding without performing transform precoding.

[0500] A resource mapper (1050) can map the modulation symbols of each antenna port to a time-frequency resource. The time-frequency resource may include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. A signal generator (1060) generates a radio signal from the mapped modulation symbols, and the generated radio signal can be transmitted to another device through each antenna. To this end, the signal generator (1060) may include an Inverse Fast Fourier Transform (IFFT) module, a Cyclic Prefix (CP) inserter, a Digital-to-Analog Converter (DAC), a frequency uplink converter, etc.

[0501] The signal processing process for a received signal in a wireless device can be configured as the inverse of the signal processing process (1010–1060) of FIG. 17. For example, a wireless device (e.g., 100, 200 in FIG. 16) can receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal can be converted into a baseband signal through a signal restorer. To this end, the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a Fast Fourier Transform (FFT) module. Subsequently, the baseband signal can be restored into a codeword through a resource de-mapper process, a postcoding process, a demodulation process, and a de-scrambling process. The codeword can be restored into the original information block through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0502] FIG. 18 illustrates a wireless device according to one embodiment of the present disclosure. The wireless device may be implemented in various forms depending on the use-example / service (see FIG. 15). 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.

[0503] Referring to FIG. 18, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 16 and may be composed of various elements, components, units / parts, 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 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. 16. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 16. The control unit (120) is electrically connected to the communication unit (110), the memory unit (130), and additional elements (140) and controls the general operation of the wireless device. For example, the control unit (120) may control the electrical / mechanical operation of the wireless device based on a program / code / command / information stored in the memory unit (130). Additionally, the control unit (120) may transmit information stored in the memory unit (130) to an external (e.g., another communication device) via a wireless / wired interface through the communication unit (110), or store information received from an external (e.g., another communication device) via a wireless / wired interface through the communication unit (110) in the memory unit (130).

[0504] The additional element (140) can be configured in various ways depending on the type of 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. 15, 100a), a vehicle (Fig. 15, 100b-1, 100b-2), an XR device (Fig. 15, 100c), a portable device (Fig. 15, 100d), a home appliance (Fig. 15, 100e), an IoT device (Fig. 15, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or financial device), a security device, a climate / environment device, an AI server / device (Fig. 15, 400), a base station (Fig. 15, 200), a network node, etc. Wireless devices can be used in a movable or fixed location depending on the use—e.g., service.

[0505] In FIG. 18, 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 partially 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 connected via a wire, and the control unit (120) and the first unit (e.g., 130, 140) may be connected wirelessly via the communication unit (110). Additionally, each element, component, unit / part, and / or module within the wireless device (100, 200) may include one or more additional elements. For example, the control unit (120) may be composed of one or more sets of processors. For example, the control unit (120) may be composed of a set of a communication control processor, an application processor, an Electronic Control Unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of RAM (Random Access Memory), DRAM (Dynamic RAM), ROM (Read Only Memory), flash memory, volatile memory, non-volatile memory and / or a combination thereof.

[0506] Hereinafter, an implementation example of FIG. 18 will be described in more detail with reference to the drawings.

[0507] FIG. 19 illustrates a portable device according to one embodiment of the present disclosure. The portable device may include a smartphone, a smartpad, a wearable device (e.g., a smartwatch, smart glasses), a portable computer (e.g., a laptop, etc.). The portable 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. 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.

[0508] Referring to FIG. 19, 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 part of the communication unit (110). Blocks 110 to 130 / 140a to 140c each correspond to blocks 110 to 130 / 140 of FIG. 18.

[0509] 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 the components of the portable device (100) to perform various operations. The control unit (120) may include an AP (Application Processor). The memory unit (130) can store data / parameters / programs / code / commands required for the operation of the portable device (100). Additionally, the memory unit (130) can store input / output data / information, etc. The power supply unit (140a) supplies power to the portable device (100) and may include wired / wireless charging circuits, batteries, etc. The interface unit (140b) can support the connection between the portable device (100) and other external devices. The interface unit (140b) may include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (140c) can receive or output video information / signals, audio information / signals, data, and / or information input by 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, etc.

[0510] For example, in the case of data communication, the input / output unit (140c) acquires information / signals (e.g., touch, text, voice, image, video) input from the user, and the acquired 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 another wireless device or to a base station. Additionally, the communication unit (110) can receive wireless signals from another wireless device or base station and then restore the received wireless signals to their 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).

[0511] The claims described in this specification may be combined in various ways. For example, the technical features of the method claims in this specification may be combined to be implemented as a device, and the technical features of the device claims in this specification may be combined to be implemented as a method. Furthermore, the technical features of the method claims and the technical features of the device claims in this specification may be combined to be implemented as a device, and the technical features of the method claims and the technical features of the device claims in this specification may be combined to be implemented as a method.

Claims

1. Regarding the method, The first device acquires information related to the sensing resolution; The first device includes the information related to the sensing resolution in the auxiliary information; and A method comprising the step of the first device transmitting to the second device the auxiliary information including the information related to the sensing resolution.

2. In Paragraph 1, The above auxiliary information is UE (user equipment) auxiliary information, and A method in which the above UE auxiliary information is transmitted as a dedicated RRC (radio resource control) message.

3. In Paragraph 1, The above information related to the above sensing resolution is sensing resolution requirement information, and A method in which the above-mentioned sensing resolution requirement information includes at least one of information related to high resolution, information related to medium resolution, or information related to low resolution.

4. In Paragraph 1, The above auxiliary information includes information related to the target detection range, and A method in which the information related to the target detection range comprises at least one of information related to long range detection, information related to medium range detection, or information related to short range detection.

5. In Paragraph 1, The above auxiliary information includes information related to movement speed, and The information related to the above movement speed is at least one of information related to the movement speed of a terminal, information related to the movement speed of a target sensing area, or information related to the movement speed of a target object, and A method in which the information related to the above-mentioned movement speed includes at least one of information related to high-speed movement speed, information related to medium-speed movement speed, or information related to low-speed movement speed.

6. In Paragraph 1, The above auxiliary information includes information related to sensing traffic patterns, a method.

7. In Paragraph 1, The above auxiliary information includes information related to the data collection data requirement, a method.

8. In Paragraph 1, A method comprising at least one of the above auxiliary information, which includes information related to the training data requirements of an AI / ML (artificial intelligence / machine learning) model, information related to the management data requirements of an AI / ML model, or information related to the inference data requirements of an AI / ML model.

9. In Paragraph 1, The above auxiliary information comprises traffic prediction information based on AI / ML model training, AI / ML model management, or AI / ML model inference.

10. In Paragraph 1, A method in which the above auxiliary information includes information related to the data size required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

11. In Paragraph 1, A method comprising the above auxiliary information including information related to bandwidth required for communication based on AI / ML model training, AI / ML model management, or AI / ML model inference.

12. In Paragraph 1, A method in which the above auxiliary information includes information related to the size of a trained AI / ML model or information related to the size of an updated AI / ML model.

13. In Paragraph 1, The first device above is a sensing transmission device or a sensing reception device, and The above second device is a base station or a sensing function, method.

14. In the first device, At least one transmitter / receiver; At least one processor; and The first device comprises at least one memory connected to the at least one processor and storing instructions, wherein the instructions are executed by the at least one processor: To acquire information related to the sensing resolution; Including the above information related to the above sensing resolution in the auxiliary information; and A first device that transmits the auxiliary information, including the information related to the sensing resolution, to a second device.

15. In a processing device, At least one processor; and The first device comprises at least one memory connected to the at least one processor and storing instructions, wherein the instructions are executed by the at least one processor: To acquire information related to the sensing resolution; Including the above information related to the above sensing resolution in the auxiliary information; and A processing device that transmits the auxiliary information, including the information related to the sensing resolution, to the second device.

16. A non-transient computer-readable storage medium that records instructions, When executed, the above instructions cause the first device: To acquire information related to the sensing resolution; Including the above information related to the above sensing resolution in the auxiliary information; and A non-transient computer-readable storage medium that enables a second device to transmit the auxiliary information, which includes the information related to the sensing resolution.

17. Regarding the method, A step in which the second device establishes a radio resource control (RRC) connection with the first device; and A method comprising the step of, based on the above RRC connection, the second device receiving auxiliary information including information related to sensing resolution from the first device.

18. In the second device, At least one transmitter / receiver; At least one processor; and The second device comprises at least one memory connected to the at least one processor and storing instructions, wherein the instructions are executed by the at least one processor: Establish a radio resource control (RRC) connection with the first device; and A second device that receives auxiliary information including information related to sensing resolution from the first device based on the above RRC connection.

19. In a processing device, At least one processor; and A second device comprising at least one memory connected to the at least one processor and storing instructions, wherein the instructions are executed by the at least one processor: Establish a radio resource control (RRC) connection with the first device; and A processing device that receives auxiliary information including information related to sensing resolution from the first device based on the above RRC connection.

20. A non-transient computer-readable storage medium that records instructions, When executed, the above commands cause the second device: Establish a radio resource control (RRC) connection with the first device; and A non-transient computer-readable storage medium that receives auxiliary information including information related to sensing resolution from the first device based on the above RRC connection.

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