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

Abstract

An apparatus, according to various embodiments, may detect whether the state of a related vehicle is a first state, predict the duration and remaining duration of the first state on the basis of detecting the first state, and perform a power-saving operation on the basis of at least one control parameter.

Description

Method for transmitting a message in a wireless communication system and device for the same

[0001] This relates to a method for devices and networks to transmit and receive messages in a wireless communication system and a device for doing so.

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

[0003] Sidelink (SL) refers to a communication method in which User Equipment (UE) establishes a direct link to directly exchange voice or data between terminals without passing through a Base Station (BS). SL is being considered as a solution to address the burden on base stations caused by rapidly increasing data traffic.

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

[0005] Meanwhile, as more communication devices require larger communication capacities, the need for improved mobile broadband communication compared to existing Radio Access Technology (RAT) is emerging. Accordingly, communication systems considering services or terminals sensitive to reliability and latency are being discussed; next-generation radio access technology that incorporates improved mobile broadband communication, Massive Machine Type Communication (MTC), and Ultra-Reliable and Low Latency Communication (URLC) can be referred to as new radio access technology (new RAT) or new radio (NR). Vehicle-to-everything (V2X) communication can also be supported in NR.

[0006] Figure 1 is a diagram illustrating a comparison between V2X communication based on RAT prior to NR and V2X communication based on NR.

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

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

[0009] Since then, various V2X scenarios regarding V2X communication have been presented in NR. For example, various V2X scenarios may include vehicle platooning, advanced driving, extended sensors, remote driving, etc.

[0010] For example, based on vehicle platooning, vehicles can dynamically form groups and move together. For example, to perform platoon operations based on vehicle platooning, vehicles belonging to said group can receive periodic data from the lead vehicle. For example, vehicles belonging to said group can use said periodic data to reduce or increase the distance between vehicles.

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

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

[0013] For example, based on remote driving, a remote driver or V2X application can operate or control a remote vehicle for a person unable to drive or for a remote vehicle located in a dangerous environment. For example, in cases where the route is predictable, such as in public transportation, cloud computing-based driving can be used for the operation or control of the remote vehicle. Additionally, access to a cloud-based back-end service platform, for example, can be considered for remote driving.

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

[0015] The technical problem that the present invention aims to solve is to provide a method for controlling the power of a terminal more accurately and efficiently.

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

[0017] A method according to one aspect by a first device comprises: a step of detecting whether the state of a vehicle associated with the first device is a first state; a step of predicting the duration and remaining duration of the first state based on the detection of the first state; and a step of performing a power saving operation based on at least one control parameter, wherein the at least one control parameter may have an initial value determined based on a first control parameter value determined based on the duration and may be dynamically updated based on a second control parameter value determined based on the remaining duration.

[0018] Alternatively, the duration and remaining duration may be predicted by an AI (Artificial Intelligence) model trained to predict at least one of the duration and remaining duration based on at least one of the operating state of the vehicle, the location of the vehicle, and a parking pattern associated with the location of the vehicle.

[0019] Alternatively, the value of the at least one control parameter may be dynamically updated based on the output of an AI (Artificial Intelligence) model trained to calculate at least one of the first control parameter value and the second control parameter value based on the duration and the remaining duration.

[0020] Alternatively, the second control parameter value may be dynamically updated based on the ratio between the duration and the remaining duration.

[0021] Alternatively, the at least one control parameter may include a first control parameter for a wake-up period and a second control parameter for an active period.

[0022] Alternatively, the values ​​of the first control parameter and the second control parameter may be dynamically updated based on the remaining duration and telematics-related scheduling information.

[0023] Alternatively, the above at least one control parameter may further include a trigger condition for event trigger-based wake-up.

[0024] Alternatively, the method may further include the step of triggering the event trigger-based wake-up based on the satisfaction of the trigger condition; and the step of collecting vehicle state information related to the trigger condition based on the fact that the event trigger-based wake-up is determined to be a false wake-up.

[0025] Alternatively, the trigger condition may be dynamically adjusted based on the collected vehicle status information.

[0026] According to another aspect, at least one non-transient computer-readable medium comprises instructions for performing operations when executed by at least one processor, said operations include detecting whether the state of a vehicle associated with the first device is a first state; predicting the duration and remaining duration of the first state based on the detection of the first state; and performing a power-saving operation based on at least one control parameter, said at least one control parameter having an initial value determined based on a first control parameter value determined based on the duration, and being dynamically updated based on a second control parameter value determined based on the remaining duration.

[0027] According to another aspect, the first device comprises: a Radio Frequency (RF) transceiver; and a processor connected to the RF transceiver, wherein the processor controls the RF transceiver to detect whether the state of a vehicle associated with the first device is a first state, predicts the duration and remaining duration of the first state based on the detection of the first state, and performs a power saving operation based on at least one control parameter, wherein the at least one control parameter may have an initial value determined based on a first control parameter value determined based on the duration and may be dynamically updated based on a second control parameter value determined based on the remaining duration.

[0028] According to another aspect, a processing device controlling a first device comprises at least one processor; and at least one memory connected to the at least one processor and storing instructions that perform operations when executed by the at least one processor, wherein the operations include causing the first device to: detect whether the state of a vehicle associated with the first device is a first state; predict the duration and remaining duration of the first state based on the detection of the first state; and perform a power saving operation based on at least one control parameter, wherein the at least one control parameter may have an initial value determined based on a first control parameter value determined based on the duration and may be dynamically updated based on a second control parameter value determined based on the remaining duration.

[0029] A method by a network according to another aspect comprises: receiving state information related to a vehicle in which a first state is detected from a first device; predicting the duration of the first state based on the state information; and transmitting power setting information to the first device, the power setting information including at least one control parameter for a power saving operation of the first device, wherein the power setting information may include the at least one control parameter configured such that the parameter value is dynamically adjusted based on the remaining duration of the first state.

[0030] A network according to another aspect comprises an RF (Radio Frequency) transceiver; and a processor connected to the RF transceiver, wherein the processor controls the RF transceiver to receive state information related to a vehicle in which a first state is detected from a first device, predicts the duration of the first state based on the state information, and transmits power setting information to the first device including at least one control parameter for a power saving operation of the first device, and the power setting information may include the at least one control parameter configured such that the parameter value is dynamically adjusted based on the remaining duration of the first state.

[0031] According to various embodiments, the power of a terminal can be controlled more accurately and efficiently in a wireless communication system. According to one example, the power consumption of the first device can be effectively reduced throughout the parking period by dynamically updating control parameter values ​​for power saving operations based on vehicle status information and parking patterns related to itself.

[0032] The effects obtainable from various embodiments are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description below.

[0033] The drawings attached to this specification are intended to provide an understanding of the present invention, to illustrate various embodiments of the invention, and to explain the principles of the invention together with the description in the specification.

[0034] Figure 1 is a diagram illustrating a comparison between V2X communication based on RAT prior to NR and V2X communication based on NR.

[0035] Figure 2 shows the structure of an LTE system.

[0036] Figure 3 shows the structure of the NR system.

[0037] Figure 4 shows the structure of a wireless frame of NR.

[0038] Figure 5 shows the slot structure of an NR frame.

[0039] FIG. 6 shows a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure.

[0040] FIG. 7 shows an electromagnetic spectrum according to one embodiment of the present disclosure.

[0041] FIG. 8 shows an example of a typical NTN scenario based on a transparent payload according to one embodiment of the present disclosure.

[0042] FIG. 9 shows an example of a typical NTN scenario based on a regenerative payload according to one embodiment of the present disclosure.

[0043] FIG. 10 shows an example of a sensing operation according to one embodiment of the present disclosure.

[0044] Figure 11 shows the radio protocol architecture for SL communication.

[0045] Figure 12 shows a terminal performing V2X or SL communication.

[0046] Figure 13 shows a resource unit for V2X or SL communication.

[0047] FIG. 14 shows an example of a BWP according to one embodiment of the present disclosure.

[0048] FIG. 15 illustrates a procedure in which a terminal performs V2X or SL communication according to a resource allocation mode, according to one embodiment of the present disclosure.

[0049] FIG. 16 is a diagram illustrating how a terminal sets or updates a power saving policy based on the parking status of a vehicle.

[0050] FIG. 17 is a diagram illustrating how the first device performs a power saving operation.

[0051] FIG. 18 is a diagram illustrating how a network supports a power saving operation of a first device.

[0052] FIG. 19 illustrates a communication system to which the present invention is applied.

[0053] FIG. 20 illustrates a wireless device that can be applied to the present invention.

[0054] FIG. 21 illustrates another example of a wireless device to which the present invention applies. The wireless device may be implemented in various forms depending on the use-example / service.

[0055] FIG. 22 illustrates a vehicle or autonomous vehicle to which the present invention is applied.

[0056] A wireless communication system is a multiple access system that supports communication with multiple users by sharing available system resources (e.g., bandwidth, transmission power, etc.). Examples of multiple access systems include CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), SC-FDMA (single carrier frequency division multiple access), and MC-FDMA (multi carrier frequency division multiple access) systems.

[0057] Sidelink refers to a communication method in which User Equipment (UE) establishes a direct link to directly exchange voice or data between terminals without passing through a Base Station (BS). Sidelink is being considered as a solution to address the burden on base stations caused by rapidly increasing data traffic.

[0058] V2X (vehicle-to-everything) refers to a communication technology that exchanges information with other vehicles, pedestrians, and infrastructure-equipped objects through wired or wireless communication. V2X can be classified into four types: V2V (vehicle-to-vehicle), V2I (vehicle-to-infrastructure), V2N (vehicle-to-network), and V2P (vehicle-to-pedestrian). V2X communication can be provided through PC5 interfaces and / or Uu interfaces.

[0059] Meanwhile, as more communication devices require larger communication capacities, the need for improved mobile broadband communication compared to existing Radio Access Technology (RAT) is emerging. Accordingly, communication systems considering services or terminals sensitive to reliability and latency are being discussed; next-generation radio access technology that incorporates improved mobile broadband communication, Massive MTC, and URLLC (Ultra-Reliable and Low Latency Communication) can be referred to as new radio access technology (new RAT) or new radio (NR). Vehicle-to-everything (V2X) communication can also be supported in NR.

[0060] The following technologies can be used in various wireless communication systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access). CDMA can be implemented using wireless technologies such as UTRA (universal terrestrial radio access) or CDMA2000. TDMA can be implemented using wireless technologies such as GSM (global system for mobile communications), GPRS (general packet radio service), and EDGE (enhanced data rates for GSM evolution). OFDMA can be implemented using wireless technologies such as IEEE (institute of electrical and electronics engineers) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, and E-UTRA (evolved UTRA). IEEE 802.16m is an evolution of IEEE 802.16e and provides backward compatibility with systems based on IEEE 802.16e. UTRA is part of UMTS (universal mobile telecommunications system). 3GPP (3rd generation partnership project) LTE (long term evolution) is part of E-UMTS (evolved UMTS) which uses E-UTRA (evolved-UMTS terrestrial radio access), employing OFDMA in the downlink and SC-FDMA in the uplink.LTE-A (advanced) is an evolution of 3GPP LTE.

[0061] 5G NR is a successor technology to LTE-A 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.

[0062] For clarity of explanation, the description focuses on LTE-A or 5G NR, but the technical concept of the embodiment(s) is not limited thereto.

[0063] Figure 2 shows the structure of an applicable LTE system. This can be called an E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network), or an LTE (Long Term Evolution) / LTE-A system.

[0064] Referring to FIG. 2, the E-UTRAN includes a base station (20; Base Station, BS) that provides a control plane and a user plane to a terminal (10). The terminal (10) may be fixed or mobile and may be referred to by other terms such as MS (Mobile Station), UT (User Terminal), SS (Subscriber Station), MT (Mobile Terminal), or Wireless Device. The base station (20) refers to a fixed station that communicates with the terminal (10) and may be referred to by other terms such as eNB (evolved-NodeB), BTS (Base Transceiver System), or Access Point.

[0065] Base stations (20) can be connected to each other through an X2 interface. The base station (20) is connected to the EPC (Evolved Packet Core, 30) through the S1 interface, more specifically to the MME (Mobility Management Entity) through the S1-MME and to the S-GW (Serving Gateway) through the S1-U.

[0066] The EPC (30) consists of an MME, an S-GW, and a P-GW (Packet Data Network-Gateway). The MME holds information regarding the terminal's connection information or capabilities, and this information is primarily used for managing the terminal's mobility. The S-GW is a gateway with an E-UTRAN as its endpoint, and the P-GW is a gateway with a PDN as its endpoint.

[0067] The layers of the Radio Interface Protocol between a terminal and a network can be classified into L1 (Layer 1), L2 (Layer 2), and L3 (Layer 3) based on the lower three layers of the Open System Interconnection (OSI) model, which is widely known in communication systems. Among these, the Physical Layer, belonging to Layer 1, provides Information Transfer Services using a physical channel, while the Radio Resource Control (RRC) layer, located at Layer 3, performs the role of controlling radio resources between the terminal and the network. To this end, the RRC layer exchanges RRC messages between the terminal and the base station.

[0068] Figure 3 shows the structure of the NR system.

[0069] Referring to FIG. 3, the NG-RAN may include gNBs and / or eNBs that provide user plane and control plane protocol termination to terminals. FIG. 7 illustrates a case where only gNBs are included. The gNBs and eNBs are connected to each other via Xn interfaces. The gNBs and eNBs are connected to the 5G Core Network (5GC) via NG interfaces. More specifically, they are connected to the access and mobility management function (AMF) via NG-C interfaces and to the user plane function (UPF) via NG-U interfaces.

[0070] Figure 4 shows the structure of a wireless frame of NR.

[0071] Referring to FIG. 4, radio frames can be used for uplink and downlink transmission in NR. The radio frame has a length of 10 ms and can be defined as two 5 ms half-frames (HF). A half-frame may contain five 1 ms subframes (SF). A subframe may be divided into one or more slots, and the number of slots within a subframe may be determined by the subcarrier spacing (SCS). Each slot may contain 12 or 14 OFDM(A) symbols according to the cyclic prefix (CP).

[0072] When normal CP is used, each slot may contain 14 symbols. When extended CP is used, each slot may contain 12 symbols. Here, 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).

[0073] Table 1 below shows the number of symbols per slot ((N) according to the SCS setting (u) when normal CP is used. slot symb ), number of slots per frame((N frame,u slot ) and the number of slots per subframe((N subframe,u slot ) is an example.

[0074] SCS (15*2 u )N slot symb N frame,u slot N subframe,u slot 15KHz (u=0)1410130KHz (u=1)1420260KHz (u=2)14404120KHz (u=3)14808240KHz (u=4)1416016

[0075] Table 2 shows the number of symbols per slot, the number of slots per frame, and the number of slots per subframe according to the SCS when an extended CP is used.

[0076] SCS (15*2 u )N slot symb N frame,u slot N subframe,u slot 60KHz (u=2)12404

[0077] In an NR system, the OFDM(A) numerology (e.g., SCS, CP length, etc.) can be configured differently among multiple cells that are merged into a single terminal. Accordingly, the (absolute time) interval of a time resource (e.g., subframe, slot, or TTI) (collectively referred to as TU (Time Unit) for convenience) composed of the same number of symbols can be configured differently among the merged cells.

[0078] In NR, multiple numerologies or SCSs may be supported to support various 5G 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. If the SCS is 60 kHz or higher, a bandwidth greater than 24.25 GHz may be supported to overcome phase noise.

[0079] The NR frequency band can be defined by two types of frequency ranges. The two types of frequency ranges may be FR1 and FR2. The numerical values ​​of the frequency ranges may change, for example, as shown in Table 3 below. Among the frequency ranges used in an NR system, FR1 may mean "sub 6GHz range" and FR2 may mean "above 6GHz range" and may be referred to as millimeter wave (mmW).

[0080] Frequency Range designationCorresponding frequency rangeSubcarrier Spacing (SCS)FR1450MHz - 6000MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0081] As described above, the numerical value of the frequency range of the NR system may change. For example, FR1 may include a band of 410 MHz to 7125 MHz as shown in Table 4 below. That is, FR1 may include a frequency band of 6 GHz (or 5850, 5900, 5925 MHz, etc.) or higher. For example, the frequency band of 6 GHz (or 5850, 5900, 5925 MHz, etc.) or higher included within FR1 may include an unlicensed band. The unlicensed band may be used for various purposes, for example, for communication for vehicles (e.g., autonomous driving).

[0082] Frequency Range designationCorresponding frequency rangeSubcarrier Spacing (SCS)FR1410MHz - 7125MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0083] Figure 5 shows the slot structure of an NR frame.

[0084] Referring to FIG. 5, a slot contains multiple symbols in the time domain. For example, in the case of a normal CP, one slot may contain 14 symbols, but in the case of an extended CP, one slot may contain 12 symbols. Alternatively, in the case of a normal CP, one slot may contain 7 symbols, but in the case of an extended CP, one slot may contain 6 symbols.

[0085] A carrier includes multiple subcarriers in the frequency domain. A Resource Block (RB) can be defined as multiple (e.g., 12) consecutive subcarriers in the frequency domain. A Bandwidth Part (BWP) can be defined as multiple consecutive (P)RBs ((Physical) Resource Blocks) in the frequency domain and can correspond to a single numerology (e.g., SCS, CP length, etc.). A carrier can include up to N (e.g., 5) BWPs. Data communication can be performed through the active BWPs. Each element can be referred to as a Resource Element (RE) in a resource grid and can be mapped to a single complex symbol.

[0086] Meanwhile, a wireless interface between terminals or a wireless interface between a terminal and a network may be composed of L1, L2, and L3 layers. In various embodiments of the present disclosure, L1 layer may refer to the physical layer. Additionally, for example, L2 layer may refer to at least one of the MAC layer, RLC layer, PDCP layer, and SDAP layer. Additionally, for example, L3 layer may refer to the RRC layer.

[0087] 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 can be combined with various embodiments of the present disclosure.

[0088] New network characteristics in 6G may be as follows.

[0089] - Satellite Integrated Network

[0090] - Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is innovative and will update wireless evolution from "connected things" to "connected intelligence." AI can be applied at each stage of the communication process (or at each step of the signal processing described below).

[0091] - Seamless integration of wireless information and energy transfer

[0092] - Ubiquitous Super 3D Connectivity: Connectivity to the network and core network functions of drones and very low Earth orbit satellites will create Super 3D connectivity in 6G ubiquitous.

[0093] Some general requirements regarding the new network characteristics of 6G mentioned above may be as follows.

[0094] - Small cell networks

[0095] - Ultra-dense heterogeneous network

[0096] - High-capacity backhaul

[0097] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communication is one of the functions of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0098] - Softwarization and virtualization

[0099] The core implementation technologies of the 6G system are described below.

[0100] - 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. In other words, 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.

[0101] - 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.

[0102] FIG. 7 illustrates an electromagnetic spectrum according to one embodiment of the present disclosure. The embodiment of FIG. 7 may be combined with various embodiments of the present disclosure. Key characteristics of THz communication include (i) a 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 techniques that can overcome range limitations.

[0103] - Large-scale MIMO technology

[0104] - Hologram beamforming (HBF)

[0105] - Optical wireless technology

[0106] - Free Space Optical Transmission Backhaul Network (FSO backhaul network)

[0107] - Quantum communication

[0108] - Cell-free communication

[0109] - Integration of wireless information and power transmission

[0110] - Integration of wireless communication and sensing

[0111] - Integrated access and backhaul network

[0112] - Big data analysis

[0113] - Reconfigurable intelligent metasurface

[0114] - Metaverse

[0115] - blockchain

[0116] - Unmanned Aerial Vehicle (UAV): UAVs or drones will be a critical element in 6G wireless communication. In most cases, high-speed data wireless connectivity can be provided using UAV technology. Base station (BS) entities can be installed on UAVs to provide cellular connectivity. UAVs can possess specific features not found in fixed BS infrastructure, such as easy deployment, robust line-of-sight links, and controlled degrees of freedom for mobility. During emergencies, such as natural disasters, the deployment of ground communication infrastructure is not economically feasible, and sometimes services cannot be provided in volatile environments. UAVs can easily handle these situations. UAVs will become a new paradigm in the field of wireless communication. This technology facilitates the three fundamental requirements of wireless networks: eMBB, URLLC, and mMTC. UAVs can also support various purposes, such as enhancing network connectivity, fire detection, disaster emergency services, security and surveillance, pollution monitoring, parking monitoring, and accident monitoring. Therefore, UAV technology is recognized as one of the most critical technologies for 6G communication.

[0117] - Autonomous Driving (Self-Driving): V2X (Vehicle to Everything), a core element in building autonomous driving infrastructure, refers to technologies that enable vehicles to communicate and share with various elements on the road for autonomous driving, such as wireless communication between vehicles (Vehicle to Vehicle, V2V) and between vehicles and infrastructure (Vehicle to Infrastructure, V2I). Fast transmission speeds and low-latency technologies are essential to maximize autonomous driving performance and ensure high safety. Furthermore, future autonomous driving may go beyond merely delivering warning or guidance messages to the driver to actively intervene in vehicle operation and directly control the vehicle in dangerous situations. Since the amount of information to be transmitted and received may become massive for this purpose, it is expected that 6G will be able to maximize autonomous driving through faster transmission speeds and lower latency compared to 5G.

[0118] - Non-terrestrial networks (NTN): An NTN may represent a network or network segment that uses radio frequency (RF) resources mounted on a satellite (or unmanned aerial system (UAS) platform). FIG. 8 illustrates an example of a typical NTN scenario based on a transparent payload according to one embodiment of the present disclosure. FIG. 9 illustrates an example of a typical NTN scenario based on a regenerative payload according to one embodiment of the present disclosure. The embodiment of FIG. 8 or FIG. 9 may be combined with various embodiments of the present disclosure. Referring to FIG. 8, the satellite (or UAS platform) may establish a service link with a UE. The satellite (or UAS platform) may be connected to a gateway via a feeder link. The satellite may be connected to a data network via the gateway. A beam footprint may refer to an area where signals transmitted by the satellite can be received. Referring to FIG. 9, a satellite (or UAS platform) can establish a service link with a UE. A satellite (or UAS platform) connected to a UE can be connected to another satellite (or UAS platform) via inter-satellite links (ISL). Another satellite (or UAS platform) can be connected to a gateway via a feeder link. Based on a replay payload, the satellite can be connected to a data network via another satellite and a gateway. If no ISL exists between the satellite and another satellite, a feeder link between the satellite and the gateway may be required. FIG. 8 and FIG. 9 are merely examples of NTN scenarios, and NTN can be implemented based on various scenarios.For example, a satellite (or UAS platform) may implement a transparent or regenerative (with on-board processing) payload. For example, a satellite (or UAS platform) may generate multiple beams across a designated service area depending on the satellite's (or UAS platform's) field of view. For example, the satellite's (or UAS platform's) field of view may vary depending on the on-board antenna diagram and the minimum elevation angle. For example, a transparent payload may include radio frequency filtering, frequency conversion, and amplification. Thus, the waveform signal repeated by the payload may not be altered. For example, a regenerative payload may include radio frequency filtering, frequency conversion and amplification, demodulation / decoding, switching and / or routing, and coding / modulation. For example, a regenerative payload may be substantially equivalent to carrying all or part of the base station functions on the satellite (or UAS platform).

[0119] - Integrated Sensing and Communication (ISAC): Radio sensing is a technology that uses radio frequencies to determine the instantaneous linear velocity, angle, and distance (range) of an object, thereby obtaining information about the characteristics of the environment and / or objects within the environment. Since radio frequency sensing capabilities do not require connecting to objects via devices within a network, they can provide services for object location determination without the need for devices. 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 utilize non-3GPP type sensors (e.g., radar, cameras) to further support 3GPP-based sensing. For example, the operation of a wireless sensing service, i.e., the sensing operation, may depend on the transmission, reflection, and scattering processing of wireless sensing signals. Thus, wireless sensing can provide an opportunity to enhance existing communication systems from communication networks to wireless communication and sensing networks. FIG. 10 illustrates an example of a sensing operation according to one embodiment of the present disclosure. The embodiment of FIG. 10 may be combined with various embodiments of the present disclosure. Specifically, FIG. 10 (a) illustrates an example of sensing using a sensing receiver and a sensing transmitter located at the same position (e.g., monostatic sensing), and FIG. 10 (b) illustrates an example of sensing using a separated sensing receiver and a sensing transmitter (e.g., bistatic sensing).

[0120] FIG. 11 illustrates a radio protocol architecture for SL communication. Specifically, FIG. 11 (a) shows the user plane protocol stack of NR, and FIG. 11 (b) shows the control plane protocol stack of NR.

[0121] The Sidelink Synchronization Signal (SLSS) and synchronization information are described below.

[0122] SLSS is an SL-specific sequence that may include PSSS (Primary Sidelink Synchronization Signal) and SSSS (Secondary Sidelink Synchronization Signal). The PSSS may be referred to as S-PSS (Sidelink Primary Synchronization Signal), and the SSSS may be referred to as S-SSS (Sidelink Secondary Synchronization Signal). For example, length-127 M-sequences may be used for S-PSS, and length-127 Gold sequences may be used for S-SSS. For example, a terminal may use S-PSS to detect the initial signal and obtain synchronization. For example, a terminal may use S-PSS and S-SSSS to obtain detailed synchronization and detect the synchronization signal ID.

[0123] PSBCH (Physical Sidelink Broadcast Channel) may be a (broadcast) channel through which basic (system) information that a terminal must know first is transmitted before transmitting or receiving SL signals. For example, the basic information may include information related to SLSS, Duplex Mode (DM), TDD UL / DL (Time Division Duplex Uplink / Downlink) configuration, information related to resource pools, types of applications related to SLSS, subframe offsets, broadcast information, etc. For example, to evaluate PSBCH performance, in NR V2X, the payload size of PSBCH may be 56 bits, including a 24-bit CRC.

[0124] S-PSS, S-SSS, and PSBCH may be included in a block format that supports periodic transmission (e.g., SL SS (Synchronization Signal) / PSBCH block, hereinafter S-SSB (Sidelink-Synchronization Signal Block)). The S-SSB may have the same numerology (i.e., SCS and CP lengths) as the PSCCH (Physical Sidelink Control Channel) / PSSCH (Physical Sidelink Shared Channel) within the carrier, and the transmission bandwidth may be within a (pre-)set SL BWP (Sidelink BWP). For example, the bandwidth of the S-SSB may be 11 RB (Resource Block). For example, the PSBCH may span 11 RB. Additionally, the frequency position of the S-SSB may be (pre-)set. Therefore, the terminal does not need to perform hypothesis detection at the frequency to discover the S-SSB in the carrier.

[0125] Meanwhile, in an NR SL system, multiple numerologies having different SCS and / or CP lengths may be supported. In this case, as the SCS increases, the length of the time resource for the transmitting terminal to transmit S-SSBs may decrease. Consequently, the coverage of S-SSBs may decrease. Therefore, to ensure S-SSB coverage, the transmitting terminal may transmit one or more S-SSBs to the receiving terminal within a single S-SSB transmission cycle according to the SCS. For example, the number of S-SSBs transmitted by the transmitting terminal to the receiving terminal within a single S-SSB transmission cycle may be pre-configured or configured for the transmitting terminal. For example, the S-SSB transmission cycle may be 160ms. For example, an S-SSB transmission cycle of 160ms may be supported for all SCSs.

[0126] For example, if the SCS is 15 kHz at FR1, the transmitting terminal may transmit one or two S-SSBs to the receiving terminal within one S-SSB transmission cycle. For example, if the SCS is 30 kHz at FR1, the transmitting terminal may transmit one or two S-SSBs to the receiving terminal within one S-SSB transmission cycle. For example, if the SCS is 60 kHz at FR1, the transmitting terminal may transmit one, two, or four S-SSBs to the receiving terminal within one S-SSB transmission cycle.

[0127] For example, if the SCS is 60 kHz at FR2, the transmitting terminal can transmit 1, 2, 4, 8, 16, or 32 S-SSBs to the receiving terminal within one S-SSB transmission cycle. For example, if the SCS is 120 kHz at FR2, the transmitting terminal can transmit 1, 2, 4, 8, 16, 32, or 64 S-SSBs to the receiving terminal within one S-SSB transmission cycle.

[0128] Meanwhile, when the SCS is 60 kHz, two types of CP may be supported. Additionally, depending on the CP type, the structure of the S-SSB transmitted by the transmitting terminal to the receiving terminal may differ. For example, the CP type may be Normal CP (NCP) or Extended CP (ECP). Specifically, for example, if the CP type is NCP, the number of symbols mapping PSBCH within the S-SSB transmitted by the transmitting terminal may be 9 or 8. On the other hand, for example, if the CP type is ECP, the number of symbols mapping PSBCH within the S-SSB transmitted by the transmitting terminal may be 7 or 6. For example, PSBCH may be mapped to the first symbol within the S-SSB transmitted by the transmitting terminal. For example, the receiving terminal receiving the S-SSB may perform Automatic Gain Control (AGC) operation during the first symbol interval of the S-SSB.

[0129] Figure 12 shows a terminal performing V2X or SL communication.

[0130] Referring to FIG. 12, in V2X or SL communication, the term terminal may primarily refer to a user's terminal. However, if network equipment such as a base station transmits and receives signals according to the communication method between terminals, the base station may also be considered a type of terminal. For example, terminal 1 may be a first device (100), and terminal 2 may be a second device (200).

[0131] For example, terminal 1 can select a resource unit corresponding to a specific resource within a resource pool, which represents a set of resources. Then, terminal 1 can transmit an SL signal using the said resource unit. For example, terminal 2, which is a receiving terminal, can be configured with a resource pool in which terminal 1 can transmit a signal, and can detect terminal 1's signal within said resource pool.

[0132] Here, if terminal 1 is within the connection range of the base station, the base station may inform terminal 1 of the resource pool. On the other hand, if terminal 1 is outside the connection range of the base station, another terminal may inform terminal 1 of the resource pool, or terminal 1 may use a pre-configured resource pool.

[0133] Generally, a resource pool can be composed of multiple resource units, and each terminal can select one or more resource units to use for its SL signal transmission.

[0134] Figure 13 shows a resource unit for V2X or SL communication.

[0135] Referring to FIG. 13, the total frequency resources of the resource pool can be divided into NF units, and the total time resources of the resource pool can be divided into NT units. Thus, a total of NF * NT resource units can be defined within the resource pool. FIG. 13 illustrates an example where the resource pool is repeated in a period of NT subframes.

[0136] As shown in FIG. 13, a single resource unit (e.g., Unit #0) may appear repeatedly over time. Alternatively, to obtain diversity effects in the time or frequency dimension, the index of the physical resource unit to which a single logical resource unit is mapped may change in a predetermined pattern over time. In this structure of resource units, a resource pool may refer to a set of resource units that a terminal intending to transmit an SL signal can use for transmission.

[0137] Resource pools can be subdivided into several types. For example, depending on the content of the SL signals transmitted from each resource pool, resource pools can be classified as follows.

[0138] (1) A Scheduling Assignment (SA) may be a signal containing information such as the location of the resource used by the transmitting terminal for transmission of the SL data channel, the Modulation and Coding Scheme (MCS) or Multiple Input Multiple Output (MIMO) transmission method required for demodulation of the data channel, and Timing Advance (TA). The SA may also be multiplexed and transmitted together with the SL data on the same resource unit, in which case the SA resource pool may refer to a resource pool in which the SA is multiplexed and transmitted together with the SL data. The SA may also be called the SL control channel.

[0139] (2) A Physical Sidelink Shared Channel (PSSCH) may be a resource pool used by a transmitting terminal to transmit user data. If SA is multiplexed and transmitted along with SL data on the same resource unit, only the form of the SL data channel excluding SA information can be transmitted from the resource pool for the SL data channel. In other words, REs (Resource Elements) that were used to transmit SA information on individual resource units within the SA resource pool can still be used to transmit SL data in the resource pool of the SL data channel. For example, the transmitting terminal can transmit by mapping the PSSCH to a succession of PRBs.

[0140] (3) The discovery channel may be a resource pool for a transmitting terminal to transmit information such as its ID. Through this, the transmitting terminal can enable adjacent terminals to discover it.

[0141] Even if the content of the SL signal described above is the same, different resource pools may be used depending on the transmission and reception attributes of the SL signal. For example, even if the same SL data channel or discovery message is used, it may be divided into different resource pools depending on the method of determining the transmission timing of the SL signal (e.g., whether it is transmitted at the time of reception of the synchronization reference signal or whether it is transmitted by applying a certain timing advance at the time of reception), the method of resource allocation (e.g., whether the base station assigns the transmission resource of an individual signal to the individual transmission terminal or whether the individual transmission terminal selects the individual signal transmission resource itself from within the resource pool), the signal format (e.g., the number of symbols occupied by each SL signal in one subframe, or the number of subframes used for the transmission of one SL signal), the signal strength from the base station, the transmission power strength of the SL terminal, etc.

[0142] FIG. 14 illustrates an example of a BWP according to an embodiment of the present disclosure. The embodiment of FIG. 14 may be combined with various embodiments of the present disclosure. In the embodiment of FIG. 14, it is assumed that there are three BWPs.

[0143] Referring to FIG. 14, the common resource block (CRB) may be a numbered carrier resource block extending from one end of the carrier band to the other. And, the PRB may be a numbered resource block within each BWP. Point A may indicate a common reference point for the resource block grid.

[0144] A BWP can be configured by point A, an offset from point A (NstartBWP), and a bandwidth (NsizeBWP). 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 on that carrier) is aligned. For example, the offset may be the PRB interval between the lowest subcarrier in a given numerology and point A. For example, the bandwidth may be the number of PRBs in a given numerology.

[0145] SLSS (Sidelink Synchronization Signal) is a sidelink-specific sequence and may include PSSS (Primary Sidelink Synchronization Signal) and SSSS (Secondary Sidelink Synchronization Signal). The PSSS may be referred to as S-PSS (Sidelink Primary Synchronization Signal), and the SSSS may be referred to as S-SSS (Sidelink Secondary Synchronization Signal). For example, length-127 M-sequences may be used for S-PSS, and length-127 Gold sequences may be used for S-SSS. For example, a terminal may use S-PSS to detect the initial signal and obtain synchronization. For example, a terminal may use S-PSS and S-SSSS to obtain detailed synchronization and detect the synchronization signal ID.

[0146] The PSBCH (Physical Sidelink Broadcast Channel) may be a (broadcast) channel through which basic (system) information that the terminal must know first is transmitted before transmitting or receiving SL signals. For example, the basic information may include information related to SLSS, Duplex Mode (DM), TDD UL / DL (Time Division Duplex Uplink / Downlink) configuration, information related to resource pools, types of applications related to SLSS, subframe offsets, broadcast information, etc. For example, to evaluate PSBCH performance, in NR V2X, the payload size of the PSBCH may be 56 bits, including a 24-bit CRC (Cyclic Redundancy Check).

[0147] S-PSS, S-SSS, and PSBCH may be included in a block format that supports periodic transmission (e.g., SL SS (Synchronization Signal) / PSBCH block, hereinafter S-SSB (Sidelink-Synchronization Signal Block)). The S-SSB may have the same numerology (i.e., SCS and CP lengths) as the PSCCH (Physical Sidelink Control Channel) / PSSCH (Physical Sidelink Shared Channel) within the carrier, and the transmission bandwidth may be within a (pre-)set SL BWP (Sidelink BWP). For example, the bandwidth of the S-SSB may be 11 RB (Resource Block). For example, the PSBCH may span 11 RB. Additionally, the frequency position of the S-SSB may be (pre-)set. Therefore, the terminal does not need to perform hypothesis detection at the frequency to discover the S-SSB in the carrier.

[0148] FIG. 15 illustrates a procedure in which a terminal performs V2X or SL communication according to a resource allocation mode, according to one embodiment of the present disclosure. The embodiment of FIG. 15 may be combined with various embodiments of the present disclosure.

[0149] Referring to FIG. 15(a), in resource allocation mode 1, the base station may schedule SL resources to be used by the terminal for SL transmission. For example, in step S1500, the base station may transmit information related to SL resources and / or information related to UL resources to the first terminal. For example, the UL resources may include PUCCH resources and / or PUSCH resources. For example, the UL resources may be resources for reporting SL HARQ feedback to the base station.

[0150] For example, the first terminal may receive information related to a dynamic grant (DG) resource and / or information related to a configured grant (CG) resource from the base station. For example, the CG resource may include a CG type 1 resource or a CG type 2 resource. In this specification, the DG resource may be a resource that the base station sets / assigns to the first terminal via downlink control information (DCI). In this specification, the CG resource may be a (periodic) resource that the base station sets / assigns to the first terminal via DCI and / or RRC messages. For example, in the case of a CG type 1 resource, the base station may transmit an RRC message containing information related to the CG resource to the first terminal. For example, in the case of a CG type 2 resource, the base station may transmit an RRC message containing information related to the CG resource to the first terminal, and the base station may transmit DCI related to the activation or release of the CG resource to the first terminal.

[0151] In step S1510, the first terminal may transmit a PSCCH (e.g., Sidelink Control Information or 1st-stage SCI) to the second terminal based on the resource scheduling. In step S1520, the first terminal may transmit a PSSCH (e.g., 2nd-stage SCI, MAC PDU, data, etc.) associated with the PSCCH to the second terminal. In step S1530, the first terminal may receive a PSFCH associated with the PSCCH / PSSCH from the second terminal. For example, HARQ feedback information (e.g., NACK information or ACK information) may be received from the second terminal via the PSFCH. In step S1540, the first terminal may transmit / report the HARQ feedback information to the base station via a PUCCH or PUSCH. For example, the HARQ feedback information reported to the base station may be information generated by the first terminal based on HARQ feedback information received from the second terminal. For example, the HARQ feedback information reported to the base station may be information generated by the first terminal based on a pre-set rule. For example, the DCI may be a DCI for scheduling SL.

[0152] Referring to FIG. 15(b), in resource allocation mode 2, the terminal can determine an SL transmission resource within an SL resource set by the base station / network or a preset SL resource. For example, the set SL resource or the preset SL resource may be a resource pool. For example, the terminal may autonomously select or schedule a resource for SL transmission. For example, the terminal may perform SL communication by selecting a resource itself within the set resource pool. For example, the terminal may select a resource itself within a selection window by performing a sensing and resource (re)selection procedure. For example, the sensing may be performed on a subchannel basis. For example, in step S1510, the first terminal, having selected a resource itself within the resource pool, may use the resource to transmit PSCCH (e.g., SCI (Sidelink Control Information) or 1st-stage SCI) to the second terminal. In step S1520, the first terminal can transmit PSSCH (e.g., 2nd-stage SCI, MAC PDU, data, etc.) associated with the PSCCH to the second terminal. In step S1530, the first terminal can receive PSFCH associated with the PSCCH / PSSCH from the second terminal.

[0153] Referring to FIG. 15 (a) or (b), for example, the first terminal may transmit an SCI to the second terminal over the PSCCH. Or, for example, the first terminal may transmit two consecutive SCIs (e.g., 2-stage SCIs) to the second terminal over the PSCCH and / or PSSCH. In this case, the second terminal may decode the two consecutive SCIs (e.g., 2-stage SCIs) to receive the PSSCH from the first terminal. In this specification, the SCI transmitted over the PSCCH may be referred to as the 1st SCI, the 1st SCI, the 1st-stage SCI, or the 1st-stage SCI format, and the SCI transmitted over the PSSCH may be referred to as the 2nd SCI, the 2nd SCI, the 2nd-stage SCI, or the 2nd-stage SCI format.

[0154] Referring to FIG. 15 (a) or (b), in step S1530, the first terminal can receive PSFCH. For example, the first terminal and the second terminal can determine a PSFCH resource, and the second terminal can use the PSFCH resource to transmit HARQ feedback to the first terminal.

[0155] Referring to FIG. 15(a), in step S1540, the first terminal can transmit SL HARQ feedback to the base station via PUCCH and / or PUSCH.

[0156] Meanwhile, the aforementioned sidelink may be defined as communication between terminals or direct communication between terminals. In this case, PSCCH may be defined as a physical control channel for communication between terminals, PSSCH as a physical data channel or physical sharing channel for communication between terminals, and PSFCH as a physical feedback transmission channel between terminals.

[0157] Meanwhile, the SoftV2X service or SoftV2X system is a system that utilizes V2X communication via a UU interface, wherein the SoftV2X server receives VRU messages or PSMs (Personal Safety Messages) from VRUs (Vulnerable Road Users) or V2X vehicles, transmits information about surrounding VRUs or vehicles based on the VRU messages or PSMs, analyzes road conditions where surrounding VRUs or vehicles are moving, and transmits messages notifying surrounding VRUs or vehicles of collision warnings based on the analyzed information. Here, the VRU message or PSM message is a message transmitted to the SoftV2X server via the UU interface and may include mobility information regarding the VRU, such as the VRU's location, direction of movement, movement path, and speed. In other words, the SoftV2X system receives mobility information of VRUs and / or vehicles related to V2X communication through the UU interface, and the SoftV2X server controls the driving paths and movement flow of VRUs, etc., based on the received mobility information via a network or similar means. Alternatively, the SoftV2X system may be configured in relation to V2N communication.

[0158] Below, a method for controlling the power of a terminal or vehicle in relation to the V2N system or V2X system described above will be explained in detail.

[0159] Adaptive power control of mobility and connectivity systems

[0160] Generally, when a vehicle is parked or remains stationary for a certain period, it may switch to sleep mode to minimize power consumption in control systems such as the ECU (Engine Control Unit) or TCU (Transmission Control Unit). Additionally, it may switch to a low-power sleep mode upon request from network devices and / or peripheral terminals. In this case, a wake-up is performed when specific conditions are met following the transition to sleep mode. The conditions for determining whether to switch to wake-up mode may be rule-based (e.g., when there is no data transmission for a certain period or when a specific event does not occur) or device signal-based (e.g., when specific conditions are met by a device attached to the vehicle, or triggers based on requests or received signals from external sensors / devices).

[0161] Despite the existence of technologies and standards for vehicle sleep / wake-up, current technology primarily utilizes methods that perform wake-up based on fixed schedules, monitoring, or external requests. Consequently, this can lead to unnecessary power consumption and instances of false wake-ups. For instance, amidst the recent active technological development of electric vehicles (EVs), connected vehicles, and autonomous vehicles, optimizing power consumption of vehicle modules—including the battery—and communication modules during parking is a critical issue, as long-term parking can result in battery discharge. This is due to the presence of functions that continuously consume power, such as the vehicle's dash cam, communication and security systems, and remote connectivity capabilities. Meanwhile, conventional vehicle battery management systems (BMS) are configured to perform only limited functions, such as monitoring battery status or providing charging warnings; consequently, they currently lack the capabilities and technologies to efficiently adjust wake-up cycles during long-term parking.

[0162] Below, we will explain in detail a method to efficiently adjust the wake-up cycle of a vehicle or a terminal / device attached to the vehicle based on an analysis of long-term parking situations.

[0163] FIG. 16 is a diagram illustrating how a terminal sets or updates a power saving policy based on the parking status of a vehicle.

[0164] Specifically, the following proposes a prediction-based performance and power control method and / or device for optimizing power control for a system of a terminal (or a terminal / device associated with a vehicle) and / or individual devices / modules / units, etc., by applying various analysis methodologies such as AI / ML in a parking state or a low-power state. For example, the terminal can adaptively adjust power saving policy parameters, including a wake-up cycle, by inputting the predicted parking time, power usage schedule, surrounding environment, patterns, device power / performance, and received external information into a trained analysis model. Additionally, the sleep mode level can be subdivided into one or more levels based on the activation and power consumption of the module, and said sleep mode level can be dynamically adjusted.

[0165] For example, the operation according to the proposed method described above can be performed in the order of (1) detection of the terminal's parking state or low power state, (2) prediction of the parking period based on pattern / state / environment information analysis, (3) optimization of learning-based power saving policy parameter settings, (4) gap analysis and policy update, and (5) model update.

[0166] (1) Parking status detection (S161)

[0167] The terminal can detect / determine whether the vehicle has entered a parking state or a low-power state by comprehensively using signals associated with the vehicle's state (whether the engine is off, whether the doors are locked, engine status, etc.), GPS, IMU, acceleration and / or CAN data, etc.

[0168] For example, the terminal may acquire one or more signals associated with the operating state of the vehicle and comprehensively analyze them to determine whether the vehicle has entered a parking state or a low-power state. Here, the signals associated with the operating state of the vehicle may include information indicating the state of the vehicle, such as whether the engine is turned on / off, whether the doors are locked / unlocked, and the engine status. Additionally, the terminal may acquire GPS information, IMU (Inertial Measurement Unit) information, acceleration sensor information, and / or CAN (Controller Area Network) data. The terminal may combine at least some of the acquired information to estimate the state related to whether the vehicle is moving, whether it remains stationary, or whether it has switched to low power, and based on the result, detect and / or determine whether the vehicle has entered a parking state or a low-power state. At this time, the terminal may improve the reliability of the judgment by comparing signals collected from multiple data sources or considering correlations, and even in cases where it is difficult to make a judgment based on specific information alone, it may use different types of sensor / vehicle state information together to more precisely determine whether the vehicle has entered a parking state or a low-power state.

[0169] (2) Prediction of parking period (S162)

[0170] To efficiently perform power control in a parking state or a low-power state, the terminal may collect information related to past parking patterns, location data, time zone information, and the driver's usage habits. By analyzing the information collected in this manner, the terminal can predict the parking period (or parking duration) of the vehicle associated with the terminal. For example, the terminal can learn stopping patterns repeatedly observed at specific locations (e.g., home, office, frequently visited restaurant, hospital, etc.) and predict the parking period associated with the vehicle by considering the average stopping time at those locations and the distribution of stopping durations by time zone. Additionally, the terminal may perform analysis based on external information to derive parking-related scenarios and roughly predict the parking period within an error range corresponding to said scenarios.

[0171] The terminal can classify various parking scenarios within a predictable range by considering scenarios belonging to general user patterns or the surrounding environment. For example, the terminal can group (cluster) parking scenarios using features such as location, time zone, and repeatability, and calculate an estimated parking period for each scenario (or cluster). Furthermore, the terminal can calculate a quantitative estimated parking time within an error range by applying AI / ML (Artificial Intelligence / Machine Learning) methodologies such as machine learning and time series analysis (e.g., Long Short-Term Memory; LSTM, etc.). For example, the terminal learns temporal correlations and repetitive patterns inherent in past data collected regarding vehicle driving, and based on this, can predict future parking periods (e.g., estimated parking time and / or its confidence interval / error range).

[0172] For example, the terminal may use information collectible from the terminal / sensor and information received from the outside as input data for predicting the parking period and / or setting power saving policy parameters. The terminal may collect at least some of the information collected internally (hereinafter “internal collected information”) and information received from an external network or surrounding terminals (hereinafter “external received information”), and comprehensively analyze them to classify parking scenarios or calculate the estimated parking time. Specifically, examples of analysis parameters that the terminal can use when training a model to predict the parking period are as follows.

[0173] 1) Information collectible from terminals / sensors (internal collected information)

[0174] The terminal can obtain the following information through sensors and the vehicle / terminal internal interface.

[0175] - Terminal status information (or, vehicle status information connected to the terminal): May include information indicating the current status, such as performance / status information by system and / or module (component) of the terminal, temperature (heat) information, communication quality information, emergency light status, charging status or charging status.

[0176] - Terminal history and pattern information (or vehicle history and pattern information connected to the terminal): May include historical data such as parking patterns (e.g., commuting times, return times, etc.) and usage habits. The terminal can improve the accuracy of parking period prediction based on repeatedly observed usage patterns.

[0177] - Spatiotemporal characteristic information: May include spatiotemporal features such as location (e.g., indoor / outdoor status, user experience-based place type—home / work / hospital, etc.), time (e.g., morning / day / evening, weekday / weekend, etc.), and specific regional characteristics (e.g., near an airport, etc.). And / or, may include environmental information such as temperature (current or hourly predicted value) and weather. The terminal may reflect in predictions and policy settings the fact that the parking period may vary depending on these spatiotemporal characteristics.

[0178] - User setting information: May include user preference information (e.g., preference for battery saving mode, communication frequency, etc.) and direct user input (e.g., input of estimated parking time). The terminal can adjust power saving policy parameters to suit user preferences through the above user setting information.

[0179] - Telematics-related information: May include telematics operation plans / schedules such as OTA (Over-The-Air Update) updates, data upload schedules, and HPC (High-Performance Computing) schedules. The terminal can utilize such schedule information as an input to adjust the wake-up cycle or sleep mode level.

[0180] 2) External received information (e.g., including V2X standardization messages and / or V2N messages)

[0181] The terminal can receive external reception information through communication with a network, infrastructure, an external server, or a nearby terminal, and said external reception information may include V2X standardized messages. For example, the external reception information may include the following.

[0182] - User plan-related information: May include information related to operation plans in parking situations, such as power saving schedules of terminals around the location.

[0183] - Information related to spatiotemporal characteristics: This may include information dependent on location and environment, such as the average parking time at the relevant location and environmental conditions (hourly forecasts for temperature and weather). The terminal can use this information to reference parking period predictions even when its own historical data is insufficient.

[0184] - Information regarding external factors: May include external factors such as connected service schedules, communication channel status, frequency and / or cause of event triggers, frequency and / or cause of false wake-ups, etc.

[0185] External information can be received in various forms from servers / networks, surrounding terminals, etc., and can also be received through V2X standard messages. The terminal can predict the parking period based on information that can be collected by the terminal itself (e.g., location, time zone, past history / patterns, etc.). For instance, the terminal can predict the parking period with relatively high confidence for behaviors included in the parking pattern of the terminal or the vehicle associated with the terminal. On the other hand, if behaviors that do not belong to the parking pattern of the terminal or the vehicle associated with the terminal (e.g., parking at a location that has not been repeatedly observed) occur, the terminal can estimate a parking scenario based on external information received from the surroundings (e.g., plan sharing information, location / environmental characteristic information, etc.). For instance, as an example of a case where a parking pattern of the terminal or the vehicle associated with the terminal exists, if the vehicle is parked in the home parking lot during the usual time after work, the terminal can predict the parking period until the usual time of going to work, and in this case, weekend vehicle usage patterns can also be taken into account.

[0186] For example, as an example of a case that does not fall under the terminal's parking pattern, the terminal can roughly predict short-term parking (e.g., parking areas, supermarkets, etc.) or medium-term or longer-term parking (e.g., parking lots near airports or train stations, etc.) based on the characteristics of the parking location, even if it is not a location where the vehicle has been repeatedly parked. In this case, the terminal can calculate the accuracy of the classification and / or the accuracy / reliability of the parking period prediction together with the classification result of the parking scenario (e.g., cluster classification result). If the prediction accuracy or reliability is low, the terminal can reflect the accuracy / reliability information in the policy update or include / use it as relevant information (e.g., information for updating saving policy parameters) so that it can prepare for / accept the possibility of such misjudgment in advance when updating power saving policy parameters later.

[0187] Additionally, if the prediction accuracy or reliability is low, the terminal may request a response from the user regarding information related to the parking period. Furthermore, if it is difficult to predict the parking period, the terminal may receive and utilize power saving plans and / or policies shared from nearby terminals or the Edge / Cloud that correspond to the average parking situation at the current location.

[0188] The finally predicted parking scenario, parking time / period, and prediction accuracy (or confidence) can be used to calculate an initial configuration for pre-setting one or more parameters related to the power saving mode. For example, the terminal can determine the initial configuration values ​​of power saving policy parameters, such as the wake-up cycle, sleep mode level, and module activation policy, based on the prediction results. Additionally, the predicted parking time / period may be shared with the user according to user settings, and the user may have a function to respond to the shared prediction information. The terminal can receive the user response based on such a function and reflect it in the settings of the prediction results and / or parameters related to the power saving mode.

[0189] (3) Optimization of learning-based power saving policy parameter settings (S163)

[0190] A power saving policy may include one or more parameters related to a power mode and a power saving schedule. The terminal may dynamically adjust these parameters. The parameters may be adjusted and operated individually, or multiple parameters may be combined and operated together. Alternatively, the terminal may adjust the power mode and / or schedule by considering cases where relatively high power consumption operations are required, such as essential software updates (e.g., OTA updates) or HPC (High-Performance Computing). Alternatively, the terminal may selectively or variably determine whether to apply the power saving policy or the level of application when a user selection or a weekly period of less than a certain duration is predicted.

[0191] Alternatively, the terminal can predict the parking time (or parking period), the current system state, and / or future system state changes through optimization analysis processes such as AI / ML / RL, and derive optimized power saving policy parameters based on the prediction results. For example, the terminal can set an initial configuration based on the optimized parameters and switch to parking mode (or low-power mode) by applying a power saving policy according to the set initial configuration. To derive and / or set such optimized parameters, the terminal can perform a learning process using various analysis methodologies, including AI / ML. For example, examples of parameters requiring optimization are as follows.

[0192] 1) Power mode

[0193] The terminal may define one or more power modes for each level according to the power activation level, and accordingly, may be configured to support multiple sleep states. For example, power modes may be classified into Deep sleep mode, Light sleep mode, Partial wake-up, Full wake-up, etc., and each level may be defined and / or implemented differently depending on the preferences of the developer and / or user and / or the results of the optimization process.

[0194] The terminal can perform power mode switching not only at the entire system level but also for each detailed component unit constituting the system (e.g., system, individual module, unit, etc.). For example, the terminal may be configured to enable partial and / or selective control, which switches the power mode for only some component units.

[0195] 2) Priority

[0196] When the terminal must use limited battery / power due to various internal and / or external factors, it may selectively and / or partially perform power mode switching or select a power mode level to apply according to a priority set at the level of system components (e.g., system, module, unit, etc.). Additionally, the priority at the component level may be variably adjusted according to the current state of the terminal and / or the surrounding environment, etc.

[0197] The terminal may communicate with a server, network, or surrounding terminals while considering limited battery power due to various internal / external factors. In this case, the terminal may variably determine whether to include or omit information being transmitted or / or uploaded based on the priority of the information / data to be transmitted and / or received. For example, the terminal may selectively omit information / data with lower priority. At this time, the priority of the said information / data may also be variably adjusted according to the current state of the terminal and / or the surrounding environment.

[0198] 3) Mode switching interval

[0199] The mode switching interval may refer to the interval between each mode / state change, including sleep mode and wake-up. Depending on the parking environment, the terminal may dynamically adjust the cycle of the said interval through analysis and / or learning-based optimization.

[0200] The above interval terms may be set to have the same period, or they may be set / adjusted to different schedules. For example, each interval term adjusted within a schedule may be configured to be the same or different from each other. As an example of a case where the above interval terms are different, if the terminal predicts a long parking period of 50 hours, a schedule in which each interval is set differently may be applied, such as setting the mode switching interval schedule within the parking period to 10 hours until the first wake-up, the second interval to 15 hours, and the third interval to 25 hours.

[0201] 4) Active period / duration

[0202] The active period / duration may refer to the time during which the terminal performs module activation or monitoring / communication operations while in the active state. Similar to the mode switching interval, the terminal can dynamically adjust the said duration through analysis-based optimization.

[0203] Within a parking period, the period term may be set identically or differently. For example, if three wake-ups occur during a parking period, the terminal may set the Active period / duration corresponding to each wake-up differently, such as setting the first wake-up to operate for 20 seconds, the second wake-up to operate for 18 seconds, and the third wake-up to operate for 25 seconds as a default setting.

[0204] The above example assumes a case where the power saving policy operates within the predicted range by applying the setting values ​​(or initial setting values) calculated based on the initially predicted parking period and / or parking scenario as is. Subsequently, schedules or setting values ​​related to the power saving policy may be dynamically changed when the policy is updated due to gap analysis and analysis updates regarding the predicted range and current state upon wake-up, remaining parking time, terminal status, environmental changes, etc. Alternatively, the optimization process may operate selectively if the parking time is below a certain level or based on user preference. Furthermore, the analysis, learning, and optimization processes may be performed independently on the terminal or collaboratively with infrastructure including the cloud and servers. For example, if the terminal's power is insufficient, the terminal transmits its status and collected / sensing information to the cloud, and the cloud performs surrogate learning / analysis based on the information to calculate optimized Cycle and on-duration values ​​(e.g., parameter values ​​related to power saving policies) and then transmits them to the terminal, and the terminal can apply the received Cycle and on-duration values.

[0205] (4) Example of reinforcement learning-based parameter optimization

[0206] Various analysis methodologies can be performed to optimize mode switching schedules and parameters, and as an example, the procedure for performing reinforcement learning-based wake-up scheduling can be carried out as follows.

[0207] A Markov decision process (MDP) model can be defined to perform reinforcement learning. For example, the three parameters constituting the above model can be set as shown in the following example.

[0208] - State(S): State may include the current system / module / cell status, surrounding environment, recent wake-up cycle and active time, remaining week time (estimated), priority, OTA updates, etc.

[0209] - Action(A): Action(A) may include adjusting the mode switching interval (e.g., +1 hour, -1 hour,...), adjusting the active period (e.g., +10 seconds, -10 seconds...), and changing the power mode (e.g., maintaining sleep mode, entering deep sleep mode, etc.).

[0210] - Reward(R): Reward(R) can be defined by considering factors such as reduced power consumption (+), reduced false wake-ups (+), missing important data (-), reduced false sleep (+), and module discharge (-).

[0211] An agent defined to achieve optimization objectives and / or goals through an MDP model recognizes the current state and can select an action or sequence of actions from among available actions that maximizes the reward. Rewards can be set to have different weights applied depending on the objective. Therefore, based on the interaction between the state, actions, and rewards, the agent can develop and learn a policy that maximizes the accumulated reward / reward value.

[0212] As an algorithm for this purpose, various RL algorithms such as DQN (Deep Q-networks), PPO (Proximal Policy Optimization), and Multi-agent RL (Reinforcement Learning) may be considered, and at least one of the above algorithms may be applied considering the purpose of analysis, available data, available power, etc. For example, if there are multiple targets (systems / modules / cells, etc.) to which Power mode is applied and multiple Power mode levels, Multi-agent RL can be used to set targets at the system / module / cell level as individual agents, and the optimal behavior of each agent and / or the optimal behavior strategy of the entire system can be derived in an environment where multiple agents interact with each other. Such power saving policies and analysis levels may be optional and / or variable. In addition, the model can be trained through analysis processes such as configuring a simulation environment for learning, initial random search, experience accumulation and policy optimization, and adaptive updates. By applying a trained model, a power-saving policy can be configured to optimize the trade-off between various factors, including performance maintenance and power consumption, while considering the system's remaining parking time (estimated), and scheduling based on this policy can be performed. Meanwhile, the trained model may require prior training using sufficient data.

[0213] For example, to enable a terminal to autonomously learn a policy in the form of “operating wake-up cycles / activation times differently for each interval based on the predicted remaining time, and readjusting subsequent schedules based on errors (discrepancies) observed during operation,” the following reinforcement learning methods may be considered.

[0214] Specifically, the reinforcement learning system may define a single weekly event as a specific situation and configure the environment so that, at the start of the specific situation, it provides a prediction of the remaining time (and / or, if necessary, its uncertainty or error range), and then accumulates the actual elapsed time and observed signals (monitoring / communication results, power consumption, etc.) as time progresses. In this case, the State (S) considered in the reinforcement learning may be configured to include the predicted remaining time, the reliability or error range of the prediction, the progress rate relative to the total time (e.g., remaining ratio or progress ratio), the previous wake-up cycle and active time, the current power / battery status, surrounding environment indicators, and recent observation results (e.g., response delay or whether an event occurred). Furthermore, in reinforcement learning, the above model can be trained to receive the state as input and output an action at each decision point (e.g., the start of a specific situation, immediately after each wake-up, or the end of an active period, etc.), and the action can be configured to increase or decrease the interval (cycle) until the next wake-up, increase or decrease the duration of the next active period, or select a predefined power mode level. Additionally, the degree of discrepancy between prediction and observation can be included in the state, and the model can be trained to readjust the next cycle and / or duration based on that value. The reward can be designed to learn the balance between power saving and required responsiveness. For example, a reward can be given for a choice that reduces power consumption during the specific situation, and a penalty can be given if wake-ups become excessively frequent and unnecessary consumption increases. Conversely, a penalty can also be given if response delay increases or if the necessary action is not performed in a timely manner.Furthermore, if reward weights are set differently over time using the time progress (remaining ratio), the model can be induced to select different periods and / or durations depending on which time interval it is in (e.g., learned so that preferred behavior changes depending on the progress even in the same state).

[0215] Based on the reinforcement-learned AI / ML model as described above, the power control schedule based on the remaining week time can be readjusted as follows.

[0216] When the terminal enters a parking state, it can predict the remaining parking time using past parking history, location information, and time zone information, and can set the predicted remaining parking time as a temporal budget for power control. For example, the terminal considers the available time margin (or operational time) available in the parking state as the said budget and can schedule the frequency / duration of wake-up and active operations within the range of said budget. The terminal can divide the said temporal budget into multiple segments and apply different wake-up schedules (policy parameter settings) to each segment. For example, each segment can be distinguished according to the progress of the budget (e.g., initial / middle / late) or a pre-set ratio / threshold, and policy parameters such as the wake-up cycle and / or active duration can be set differently for each segment. For example, if the predicted remaining parking time is 10 hours, the terminal can set a relatively short wake-up cycle in the segment corresponding to the initial stage of the total budget (a specific threshold (e.g., 90%)) considering the possibility of the user returning immediately. This is because, considering that user return may occur relatively quickly immediately after parking or during the initial phase, settings to ensure responsiveness need to be prioritized. Subsequently, in the middle phase of the total budget, the wake-up cycle can be set longer than in the initial phase to prioritize power saving effects. For example, in the middle phase, policy parameters can be configured to reduce power consumption by lowering the frequency of unnecessary wake-ups. In the later phase (e.g., 10%), where the remaining budget has decreased, policy parameters can be applied to shorten the wake-up cycle again or increase the active duration, as it is determined that the likelihood of user return increases.For example, in the later sections, a reduction in the cycle and / or an increase in the active duration may be selectively applied to enable faster response or more sufficient active operation when necessary. The terminal can analyze the difference between the predicted remaining parking time and the actual elapsed time at each Wake-up point, and if the difference exceeds a predetermined range, it can recalculate the remaining Budget and dynamically update the Wake-up schedule for the subsequent sections. For example, the terminal can adjust the remaining Budget and section boundaries to correspond to cases where the actual elapsed time is faster or slower than the prediction, and accordingly reset the Wake-up cycle and / or active duration applied in the subsequent sections. Accordingly, the terminal can perform planned Wake-up control considering the entire parking period to reduce unnecessary power consumption while maintaining the necessary responsiveness. In this case, the terminal can flexibly manage the schedule through section-by-section planning and updating, taking into account the balance between power consumption and responsiveness during the parking period. The above-described embodiment is merely an example of flexibly adjusting the Wake-up schedule by dividing the predicted remaining parking time Budget by section, and the proposed method is not limited thereto. For example, the method for predicting remaining parking time, the number and ratio of segment divisions, the wake-up cycle and active duration applied in each segment, the power mode level, priority setting, policy update timing and conditions, etc., may be applied by varying or combining depending on the terminal's state, environmental information, user settings, external reception information, prediction reliability or error range, etc., and such variations may also be included within the technical concept and scope of the proposed invention.

[0217] (5) Gap Analysis and Policy Update (S164, S165, S166, S167)

[0218] While power saving is being performed according to the initial configuration of parameters set during the parking start phase, the terminal may perform a gap analysis at the time of transitioning to the wake-up state, and the result (output) of the gap analysis may be used as an input for policy updates. Conditions requiring the gap analysis may include gaps between the current state and predicted values ​​of systems, modules, or units, and gaps related to environmental factors; these conditions may be considered individually or in various combinations of multiple conditions. Furthermore, each of these conditions or separate conditions may be added or deleted depending on the operational situation.

[0219] Power saving policies can be updated by utilizing the results of the gap analysis (Output) as input. For example, if the gap is within the margin of error, the policy can be maintained, while if the gap exceeds the margin of error, the policy can be changed and / or adjusted (e.g., increased or decreased). Furthermore, depending on the terminal's status, the analysis-based policy update process can be performed on the terminal, within the infrastructure including the cloud and servers, or collaboratively by the terminal and the infrastructure. For instance, if the terminal's power is insufficient, the terminal transmits its status and collected / sensed information to the cloud, and the cloud performs surrogate learning and / or analysis based on this information to transmit optimized cycle and duration values ​​to the terminal.

[0220] Policy updates may entail additional power consumption for analysis; in this case, load balancing may be required between the power saved through the establishment and / or implementation of power-saving policies and the power required for the analysis. Furthermore, efficiency measures to reduce power consumption during analysis may include methods such as the following examples, but are not limited to these, and additional methodologies may be applied. These methods can be applied throughout the overall analysis process and may be used individually or in various combinations.

[0221] (6) Methods to improve power consumption efficiency during analysis

[0222] 1) Model lightweighting: Lightweighting techniques (e.g., model compression, model pruning, etc.) can be applied to a pre-trained model in an on-line state (high power), a simple model can be used in an off-line state, and post-updates can be performed in an on-line state.

[0223] 2) Look-up table: By inputting specific information and / or parameter values ​​into a look-up table generated based on a learned model, a mathematically calculated output can be derived.

[0224] 3) Cloud computing: Using a communication system, a model can be trained by collecting and analyzing data in the Cloud, and model updates can be transmitted to the terminal. For example, information collected and sensed by the terminal can be included in standardized V2X messages (e.g., BSM, CAM, DENM, SDSM, CPM, etc.) or converted into data and transmitted to the Cloud, and the Cloud can perform training using the received information and additional collectible information as input information.

[0225] 4) Federated learning: Collected information can be synchronized with terminals, other terminals, Cloud / Edge, etc., and cooperative learning and model updates can be performed through appropriate communication-based offloading. For example, similar to cloud computing, federated learning and / or analysis can be performed by considering power consumption for each terminal through the sharing of information collected from terminals and information that can be collected externally (including standardized messages).

[0226] 5) False wake-up filtering: By using various filtering techniques such as Kalman filters and adaptive thresholds individually and / or in combination to remove noise and consider environmental changes, unnecessary wake-up detection can be mitigated.

[0227] These methods can be configured to improve power efficiency by applying lightweight models or simplified operations based on lookup tables to minimize power consumption during analysis / learning and policy update processes, offloading analysis processing through cloud computing and / or federated learning, and reducing unnecessary wake-ups through filtering techniques.

[0228] (7) Filtering method to prevent event-based false wake-up

[0229] When performing event-trigger-based wake-ups through monitoring and received information derived from sensor detection, unnecessary wake-ups may occur due to various factors. For instance, false wake-ups may occur due to errors in detecting environmental changes, errors in detecting events, or sensor noise. Therefore, filtering techniques may be required to mitigate these unnecessary wake-up situations. Various methodologies can be used for such filtering, including Kalman filters, adaptive thresholds, and / or combinations of multiple methods. By applying these methodologies, sensor noise can be eliminated and the actual state of the vehicle can be estimated more accurately to prevent unnecessary wake-ups. Furthermore, event-based wake-up control that adapts to the situation can be performed by automatically adjusting the wake-up threshold according to environmental changes. Consequently, battery life can be extended and unnecessary power consumption minimized. Additionally, by storing and / or transmitting data regarding false wake-ups to supplement existing models, the causes of false wake-ups can be predicted, and model performance can be improved.

[0230] (8) Model Update (S168, S169)

[0231] When parking and power saving modes are terminated and power activation occurs, the model can be tuned, improved, and / or updated by additionally utilizing data collected and / or received during parking. In the long term, the accuracy of parking time prediction can be enhanced and the AI ​​model for power saving can be continuously improved by learning repeated patterns at specific locations using information collected and received from the terminal. Furthermore, the goal is to improve overall energy efficiency by reducing unnecessary power consumption through performance enhancement via continuous AI model updates and optimizing power saving policies.

[0232] As such, the proposed methods described above allow the terminal's power control system to be configured to dynamically adjust a power saving policy, including wake-up intervals or cycles, based on analysis and to optimize power during parking. The terminal can predict parking patterns and parking times based on analysis utilizing the terminal's state, environment, and received information. Furthermore, the terminal can optimize and set power saving policy parameters and control power based on said parameters, and can selectively activate modules by applying different power modes for each module. Moreover, the terminal can analyze the difference between the predicted state and the actual state and dynamically adjust the policy based on the analysis results, and can perform control to efficiently manage power consumption during the analysis process. Additionally, the terminal can perform filtering to reduce false wake-ups and continuously update the learned model and policy.

[0233] Meanwhile, although the steps in FIG. 16 are described as being divided into multiple steps for convenience of explanation, depending on the embodiment, some steps may be omitted, the order may be changed, or they may be performed by integrating with other steps, and it is natural that such variations are also included within the technical spirit and scope of the present invention.

[0234] Furthermore, the proposed methods described above can be combined in various ways. For example, the technical features of the method claims of this specification may be combined to be implemented as a device, and the technical features of the device claims of this specification may be combined to be implemented as a method. Additionally, the technical features of the method claims and the device claims of this specification may be combined to be implemented as a device, and the technical features of the method claims and the device claims of this specification may be combined to be implemented as a method. Furthermore, the objects to which the proposed methods can be applied may include not only vehicles but also various terminals, mobility and connectivity systems that consume power.

[0235] FIG. 17 is a diagram illustrating how the first device performs a power saving operation.

[0236] The first device may be mounted in a vehicle (e.g., a telematics terminal, a gateway, a domain controller, a body controller, or an embedded device within the vehicle). The first device may include a processor, memory, a communication unit, a sensing / receiving unit (for receiving vehicle status information), and a power control module (for power mode control, wake-up scheduling, etc.). The first device may receive / acquire vehicle status information (e.g., battery status, door opening / closing, vibration, location, time zone, recent parking history, event occurrence information, etc.) via an in-vehicle network (CAN / LIN / Ethernet, etc.) or an external network. Alternatively, the first device may include an AI engine (model execution unit) and / or a learning module for performing AI / ML / RL-based prediction or optimization, and may perform analysis / learning in cooperation with a server / cloud when power / computation resources are limited (e.g., the device transmits status / sensing information to a server, and the server calculates optimal parameters and transmits them to the device).

[0237] As described above, the first device can acquire state information regarding a vehicle to which the first device is attached, predict / estimate the state of the vehicle based on the acquired state information, and perform an operation to control the power of the first device (or vehicle) based on the predicted / estimated state of the vehicle. For example, the first device can control a power saving operation of the first device (and / or vehicle) based on the state information of the vehicle, as described in "Adaptive power control of mobility and connectivity systems." For example, the first device can provide the duration of the vehicle's parking state and the remaining duration as inputs to an AI model, acquire output information for at least one control parameter appropriately adjusted / updated according to the duration and remaining duration from the AI ​​model, and perform a power saving operation for the first device (and / or vehicle) based on the output information.

[0238] Here, the power saving operation may be performed based on a power saving policy, and the power saving policy may include one or more control parameters (e.g., power mode, wake-up period, active period, priority, trigger condition, etc.) set to reduce the power consumption of the first device (and / or vehicle). The control parameter values ​​may be specific setting values ​​corresponding to each of the at least one control parameter (e.g., wake-up period = 10 hours, active period = 20 seconds, power mode = Deep sleep, etc.).

[0239] Specifically, referring to FIG. 17, the first device can detect whether the vehicle's state is a first state (S171). For example, the first device can detect the first state using the vehicle's operating state (e.g., ignition OFF, speed, gear state), the vehicle's location, time zone, or parking-related signals. Here, the first state may mean that the vehicle is in a parked state (e.g., IG OFF / parking gear / parking brake / vehicle speed 0, etc.), or a specific state in which the vehicle satisfies predefined conditions (e.g., long-term parking, a state requiring low power maintenance).

[0240] Next, the first device can predict the duration and remaining duration of the first state based on the detection of the first state (S173). Here, the duration may refer to the predicted total duration (total parking period or total parking time, etc.) until the first state ends, and the remaining duration may refer to the time remaining until the end of the first state from the current point in time while the first state is in progress. The remaining duration may decrease sequentially over time and may be recalculated with an updated prediction at the time of wake-up or monitoring.

[0241] For example, the duration and / or remaining duration can be predicted by an Artificial Intelligence (AI) model. The AI ​​model may be trained to predict at least one of the duration and remaining duration based on at least one of the vehicle's operating state, the vehicle's location, and parking patterns related to the vehicle's location (e.g., average parking time at the same location, parking history by time of day / day of the week). For example, the first device may provide the AI ​​model with input information such as (i) past parking history data, (ii) parking distribution by location-time of day combination, (iii) characteristics of recent parking events, and (iv) battery status and / or environmental factors, thereby obtaining output information regarding the duration and / or remaining duration of the first state predicted by the AI ​​model. Here, the AI ​​model may be implemented in various forms, such as regression, time series forecasting, or classification-based interval forecasting. and / or, the first device may further input information regarding parking duration and / or power saving policies provided / received from peripheral devices into the AI ​​model, and may obtain prediction / output information regarding the predicted duration and / or remaining duration from the AI ​​model, with further consideration given to the parking durations of peripheral devices.

[0242] Next, the first device can perform a power saving operation based on at least one control parameter (S175). For example, the first device can switch to a parking mode (low power mode) or limit monitoring / communication operations by setting a wake-up cycle and an active period.

[0243] Alternatively, the first device may dynamically update / adjust the value of the at least one control parameter based on the predicted duration and the remaining duration. For example, the first device may determine (set) the first control parameter value determined based on the duration as the initial value of the at least one control parameter. For example, if the predicted duration is long, the initial wake-up cycle may be set to a longer duration or the power mode level may be set to a deeper power saving level. And / or, the first device may determine at least one second control parameter value based on the remaining duration and dynamically update the at least one control parameter value based on the at least one second control parameter value. For example, as the remaining duration decreases, the wake-up cycle may be shortened in stages (ensuring responsiveness), the active period may be adjusted, or the power mode level may be changed. Here, the first / second control parameter value may be a single parameter (e.g., only the wake-up cycle) or may be in the form of a vector including multiple parameters (e.g., wake-up cycle + active period + power mode). Parameters can be updated individually, or they can be combined to operate together.

[0244] Alternatively, the second control parameter value may be dynamically updated based on the ratio between the duration and the remaining duration. For example, the first device may update the second control parameter value based on a remaining ratio (or progress rate) defined as remaining duration / duration. As the remaining ratio passes a specific threshold (e.g., 90%, 50%, 10%), the wake-up cycle or active period may be set / updated differently for each interval.

[0245] Alternatively, the values ​​of the first control parameter and the second control parameter may be dynamically updated based on the remaining duration and telematics-related scheduling information. The telematics-related scheduling information may include, for example, over-the-air (OTA) software updates, remote diagnostics, remote control reservations, or scheduled information for high-power computing (HPC) required tasks. The first device may adjust a power saving policy, such as shortening the wake-up cycle or extending the active period during specific time periods, according to the scheduling information.

[0246] Alternatively, at least one control parameter may include a first control parameter for the wake-up period and a second control parameter for the active period (active duration). The wake-up period may refer to the transition interval between the sleep state and the wake-up state, and the active period may refer to the duration for performing communication / monitoring / module activation operations after waking up. The first device may divide the predicted duration (or weekly period; Budget) into multiple segments and apply / set different wake-up periods and / or active periods in each segment. Additionally, the schedule for subsequent segments may be readjusted by analyzing the discrepancy between the predicted remaining duration at the time of wake-up and the observed results.

[0247] Alternatively, such control parameter values ​​may be dynamically updated based on the output of the AI ​​model. For example, the first device may provide duration and remaining duration as input information to an AI model trained to calculate at least one of a first control parameter value and a second control parameter value. In this case, the first device may set an initial control parameter value based on the first control parameter value output by the AI ​​model, and subsequently, input information regarding the remaining duration into the AI ​​model in real-time or periodically to dynamically update the control parameter value based on the second control parameter value obtained.

[0248] Alternatively, the first device may optimize the wake-up cycle, active period, and / or power mode level using reinforcement learning (RL) of an AI model. A Markov Decision Process (MDP) model may be defined for reinforcement learning, and the State may include the predicted remaining time, prediction confidence or error range, previous wake-up history, battery status, priority, OTA schedule, etc. The Action may include increasing or decreasing the wake-up cycle and active period, selecting a power mode level, etc., and the Reward may be defined by considering the reduction of power consumption, reduction of false wake-ups, and penalties for failure to perform necessary functions. The first device may generate / update a schedule that optimizes the trade-off between responsiveness and power consumption while considering the remaining budget according to a reinforcement-learned power saving policy.

[0249] Alternatively, at least one control parameter may further include a trigger condition for event-trigger-based wake-up. The trigger condition may be defined, for example, by shock / vibration, door opening / closing, a specific CAN signal change, a communication reception event, a security event, etc. Additionally, the first device may trigger an event-trigger-based wake-up based on the satisfaction of the trigger condition. If the event-trigger-based wake-up is determined to be a false wake-up (e.g., a wake-up without a meaningful event / request), the first device may collect vehicle state information related to the trigger condition. The collected state information may include sensing values ​​immediately before / after the wake-up, environmental information, communication logs, vehicle signal sequences, etc. In this case, the first device may dynamically adjust the trigger condition based on the collected vehicle state information. For example, it may adjust a threshold value by learning / analyzing a pattern that caused a false wake-up, or variably update the trigger condition to allow the wake-up only when a specific combination of conditions is present.

[0250] In this way, the first device may be configured to acquire / interpret state information of a vehicle (vehicle system), which is an object outside the first device, and perform power control of the first device (or vehicle). For example, the first device may take vehicle domain information as input, such as the vehicle's operating state (start / IG state, transmission state, vehicle speed, door / trunk state, etc.), the vehicle's location and location-based parking pattern, and telematics-related scheduling information (OTA / remote diagnostics / reservation operation, etc.), predict the duration and remaining duration of a first state (e.g., parking state), and set / update power saving policy parameters including a wake-up cycle, active period, power mode level, and / or trigger conditions based on the prediction result. By performing vehicle state-based control in this manner, the first device can implement power control that reflects the actual usage context of the vehicle (possibility of user return, parking trends based on location / time of day, necessity of scheduled high-power operations, etc.). In addition, unlike conventional fixed schedules or simple power saving control using only internal terminal information, the vehicle state-based power control described above is synchronized with changes in the vehicle state, and control parameters can be reset continuously or in segments according to changes in the remaining duration (Budget). For example, even if the parking state is the same, the remaining parking time can vary significantly depending on the vehicle's location and parking pattern. Therefore, the first device determines initial parameter values ​​based on vehicle state information, and then dynamically updates the wake-up cycle and active period by reflecting the gap between the predicted remaining time and vehicle state signals observed during parking (e.g., whether an event occurs, communication response, environmental change, etc.). Accordingly, control is possible to reduce power consumption and the frequency of false wake-ups caused by unnecessary wake-ups, while ensuring responsiveness in segments where the likelihood of user return is high.For example, the first device can adaptively optimize the trade-off between power consumption and functional responsiveness based on external state information of the vehicle.

[0251] FIG. 18 is a diagram illustrating how a network supports a power saving operation of a first device.

[0252] The determination and optimization of the power saving policy are not limited to being performed solely by the first device; the network (e.g., server / cloud / backend system) may be configured to directly determine the power saving policy to be applied to the first device using status information collected from the vehicle and the first device, and then provide the result to the first device. For instance, since the network can integrally possess and learn operational history of multiple vehicles / multiple devices, location-time-based parking patterns, user behavior, update (OTA) schedules, and various operational environment data, it can perform policy decisions based on macroscopic patterns and long-term statistics that are difficult to reflect using only internal terminal information. Furthermore, even when the power / computational resources of the first device are limited, the network can perform prediction / optimization calculations on its behalf to provide the effect of further reducing the device's power consumption. Here, the network (server) may include a communication unit, a processor, and memory, and may communicate with the vehicle or the first device to receive vehicle status information and device-related information. The network may predict the duration and remaining duration of a first state (e.g., parking state) based on received information and stored historical data, and generate power configuration information or power saving policy information for power control of the first device according to the prediction result. The power configuration information or power saving policy information (hereinafter referred to as power configuration information) may include power mode, wake-up cycle, active period, trigger condition, priority, and / or scheduling-related parameters.

[0253] Referring to FIG. 18, the network may receive status information related to a vehicle in which a first state is detected from a first device (S181). The status information may include, for example, at least one of the vehicle's operating state (start / IG state, vehicle speed, gear state, etc.), the vehicle's location, location-based parking pattern, battery / power related status, event occurrence information, and telematics-related scheduling information (OTA / remote diagnosis / reservation operation, etc.). The status information may be transmitted periodically or upon the occurrence of an event.

[0254] The network can predict the duration of a first state based on received state information (S183). Here, the duration may refer to the total predicted time until the first state ends. The network can predict the duration by integratively utilizing past parking history, parking distribution by location and time zone, user behavior statistics, and / or external environment information, and, if necessary, can calculate the remaining duration along with the duration prediction or estimate the pattern of change of the remaining duration. Such prediction can be performed by an Artificial Intelligence (AI) model, and the AI ​​model can be trained to output the duration (and / or remaining duration) by receiving the vehicle's operating state, location, parking pattern, and operation history as input. By using a model trained on large-scale data collected from multiple terminals, the network can improve prediction accuracy and generalization performance compared to the prediction by the first device alone.

[0255] The network may generate power setting information including at least one control parameter for the power saving operation of the first device and transmit it to the first device (S185). The power setting information may include one or more parameters related to a power mode and a power saving schedule, such as a mode switching interval, an active period / duration, a power mode level, a priority, and / or an event trigger condition. Additionally, the power setting information may include at least one control parameter configured such that the parameter value is dynamically adjusted based on the remaining duration of the first state. For example, the network may configure the power setting information to include setting values ​​such that the mode switching interval and the active period are set differently by interval or changed in stages according to changes in the predicted duration (total Budget) and the remaining duration (remaining Budget). At this time, the power setting information may be configured to include (i) a set of multiple parameter values ​​corresponding to the remaining duration interval, (ii) a criterion for calculating parameter values ​​based on the ratio of the remaining duration (remaining / total), and / or (iii) update conditions (e.g., wake-up time, event occurrence time, when the prediction error exceeds a threshold value), etc.

[0256] Thus, the proposed invention enables the first device to effectively reduce power consumption throughout the parking period by dynamically updating control parameter values ​​for power saving operations based on vehicle status information and parking patterns related to itself. Furthermore, the proposed invention can maintain responsiveness to the maximum extent in sections where user return is highly likely, while reducing unnecessary wake-ups through the updating of control parameter values ​​based on vehicle status information and parking patterns. Accordingly, the proposed invention can adaptively optimize the trade-off between the power efficiency and function performance (monitoring / communication, etc.) of the first device. In addition, the proposed invention can effectively reduce the computational burden and power consumption of the first device by supporting the determination and setting of the power saving policy of the first device based on duration and remaining duration through cooperation with a network.

[0257] Example of a communication system to which the invention is applied

[0258] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods, and / or flowcharts of the invention disclosed in this document may be applied to various fields requiring wireless communication / connection (e.g., 5G) between devices.

[0259] 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.

[0260] FIG. 19 illustrates a communication system to which the present invention is applied.

[0261] Referring to FIG. 19, the communication system (1) to which the present invention applies 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)) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Thing) device (100f), and an AI 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). XR devices include AR (Augmented Reality) / VR (Virtual Reality) / MR (Mixed Reality) devices and can be implemented in the form of HMDs (Head-Mounted Devices), HUDs (Head-Up Displays) equipped in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, etc. Portable devices may include smartphones, smartpads, wearable devices (e.g., smartwatches, smart glasses), computers (e.g., laptops, etc.). Home appliances may include TVs, refrigerators, washing machines, etc. IoT devices may include sensors, smart meters, etc. For example, base stations and networks may be implemented as wireless devices, and a specific wireless device (200a) may operate as a base station / network node to other wireless devices.

[0262] 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 the 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, or a 5G (e.g., NR) network. The 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).

[0263] 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), 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 various proposals of the present invention, 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.

[0264] Example of a wireless device to which the present invention is applied

[0265] FIG. 20 illustrates a wireless device that can be applied to the present invention.

[0266] Referring to FIG. 20, 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. 19.

[0267] 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 flowcharts 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 / chipset designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (106) may be connected to the processor (102) and may transmit and / or receive wireless signals 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 invention, the wireless device may refer to a communication modem / circuit / chipset.

[0268] The first wireless device or the first device (100) may include a processor (102), a memory (104), and a transceiver (106). The memory (104) may include at least one program capable of performing operations related to the embodiments described in FIGS. 16 through 18 and "Adaptive power control of mobility and connectivity systems". The operations include the processor (102) detecting whether the state of a vehicle associated with the first device is a first state; predicting the duration and remaining duration of the first state based on the detection of the first state; and performing a power saving operation based on at least one control parameter, wherein the at least one control parameter may have an initial value determined based on a first control parameter value determined based on the duration and may be dynamically updated based on a second control parameter value determined based on the remaining duration.

[0269] Alternatively, a processing device may be configured comprising at least one processor (102) and a memory (104) for controlling the first device. In this case, the processing device may include at least one processor; and at least one memory connected to the at least one processor and storing instructions that perform operations when executed by the at least one processor. The operations include detecting whether the state of a vehicle associated with the first device is a first state; predicting the duration and remaining duration of the first state based on the detection of the first state; and performing a power saving operation based on at least one control parameter, wherein the at least one control parameter may have an initial value determined based on a first control parameter value determined based on the duration and may be dynamically updated based on a second control parameter value determined based on the remaining duration.

[0270] 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 operation sequences 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). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may 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 operation sequence diagrams disclosed in this document. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals 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 the present invention, the wireless device may refer to a communication modem / circuit / chip.

[0271] The second wireless device or network (200) may include a transceiver (206), a processor (202), and a memory (204). The memory (204) may include at least one program capable of performing operations related to the embodiments described in FIGS. 16 through 18 and "Adaptive power control of mobility and connectivity systems". The operations include the processor (202) controlling the transceiver (206) to receive state information related to a vehicle in which a first state is detected from a first device, predicting the duration of the first state based on the state information, and transmitting power setting information to the first device including at least one control parameter for a power saving operation of the first device, wherein the power setting information may include the at least one control parameter configured such that the parameter value is dynamically adjusted based on the remaining duration of the first state.

[0272] 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.

[0273] 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.

[0274] 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, codes, 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.

[0275] 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.

[0276]

[0277] Examples of wireless device applications to which the present invention is applied

[0278] FIG. 21 illustrates another example of a wireless device to which the present invention applies. The wireless device may be implemented in various forms depending on the use-example / service (see FIG. 19).

[0279] Referring to FIG. 21, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 20 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. 21. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 20. 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).

[0280] 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. 19, 100a), a vehicle (Fig. 19, 100b-1, 100b-2), an XR device (Fig. 19, 100c), a portable device (Fig. 19, 100d), a home appliance (Fig. 19, 100e), an IoT device (Fig. 19, 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. 19, 400), a base station (Fig. 19, 200), a network node, etc. Wireless devices can be used in a movable or fixed location depending on the use—e.g., service.

[0281] In FIG. 21, 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 a portion may be wirelessly connected via a communication unit (110). For example, within the wireless device (100, 200), the control unit (120) and the communication unit (110) may be wired, and the control unit (120) and the first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (110). 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.

[0282] Examples of vehicles or autonomous vehicles to which the present invention is applied

[0283] FIG. 22 illustrates a vehicle or autonomous vehicle to which the present invention applies. The vehicle or autonomous vehicle may be implemented as a mobile robot, vehicle, train, manned / unmanned aerial vehicle (AV), ship, etc.

[0284] Referring to FIG. 22, a vehicle or autonomous vehicle (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a driving unit (140a), a power supply unit (140b), a sensor unit (140c), and an autonomous driving unit (140d). The antenna unit (108) may be configured as part of the communication unit (110). Blocks 110 / 130 / 140a to 140d each correspond to blocks 110 / 130 / 140 of FIG. 21.

[0285] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, roadside base stations (Roadside units), etc.), and servers. The control unit (120) can perform various operations by controlling elements of the vehicle or autonomous vehicle (100). The control unit (120) may include an Electronic Control Unit (ECU). The driving unit (140a) can drive the vehicle or autonomous vehicle (100) on the ground. The driving unit (140a) may include an engine, motor, power train, wheels, brakes, steering device, etc. The power supply unit (140b) supplies power to the vehicle or autonomous vehicle (100) and may include wired / wireless charging circuits, batteries, etc. The sensor unit (140c) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (140c) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an inclination sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / reverse sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (140d) may implement technologies such as maintaining the driving lane, technologies for automatically adjusting speed such as adaptive cruise control, technologies for automatically driving along a predetermined path, and technologies for automatically setting a path and driving when a destination is set.

[0286] For example, the communication unit (110) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (140d) can generate an autonomous driving path and a driving plan based on the acquired data. The control unit (120) can control the drive unit (140a) so that the vehicle or the autonomous vehicle (100) moves along the autonomous driving path according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (110) can acquire the latest traffic information data from an external server non-periodically and can acquire surrounding traffic information data from surrounding vehicles. Additionally, during autonomous driving, the sensor unit (140c) can acquire vehicle status and surrounding environment information. The autonomous driving unit (140d) can update the autonomous driving path and the driving plan based on the newly acquired data / information. The communication unit (110) can transmit information regarding the vehicle location, autonomous driving path, driving plan, etc. to an external server. An external server can predict traffic information data in advance using AI technology, etc., based on information collected from vehicles or autonomous vehicles, and can provide the predicted traffic information data to vehicles or autonomous vehicles.

[0287] The wireless communication technology implemented in the wireless device (XXX, YYY) of this specification may include LTE, NR, and 6G, as well as Narrowband Internet of Things for low-power communication. 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 device (XXX, YYY) of this specification 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 device (XXX, YYY) of this specification may include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) with consideration 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.

[0288] The embodiments described above are combinations of the components and features of the present invention in a specific form. Each component or feature should be considered optional unless otherwise explicitly stated. Each component or feature may be implemented in a form not combined with other components or features. Additionally, it is possible to construct embodiments of the present invention by combining some components and / or features. The order of operations described in the embodiments of the present invention may be changed. Some components or features of one embodiment may be included in another embodiment, or may be replaced with corresponding components or features of another embodiment. It is obvious that embodiments may be constructed by combining claims that do not have an explicit citation relationship in the claims, or that new claims may be included by amendment after filing.

[0289] In this document, embodiments of the present invention are described primarily with a focus on the signal transmission and reception relationship between a terminal and a base station. This transmission and reception relationship is extended in the same or similar manner to signal transmission and reception between a terminal and a relay or between a base station and a relay. Specific operations described in this document as being performed by a base station may, in some cases, be performed by an upper node. That is, it is self-evident that various operations performed for communication with a terminal in a network consisting of multiple network nodes including a base station may be performed by the base station or other network nodes other than the base station. The base station may be replaced by terms such as fixed station, Node B, eNode B (eNB), and access point. Additionally, the terminal may be replaced by terms such as User Equipment (UE), Mobile Station (MS), and Mobile Subscriber Station (MSS).

[0290] Embodiments according to the present invention may be implemented by various means, for example, hardware, firmware, software, or a combination thereof. In the case of implementation by hardware, one embodiment of the present invention may be implemented by one or more ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, etc.

[0291] In the case of implementation by firmware or software, an embodiment of the present invention may be implemented in the form of a module, procedure, function, etc., that performs the functions or operations described above. Software code may be stored in a memory unit and executed by a processor. The memory unit may be located inside or outside the processor and may exchange data with the processor by various means already known.

[0292] It is obvious to those skilled in the art that the present invention may be embodied in other specific forms without departing from the features of the invention. Accordingly, the foregoing detailed description should not be interpreted restrictively in all respects but should be considered exemplary. The scope of the invention shall be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the invention are included within the scope of the invention.

[0293] The embodiments of the present invention as described above can be applied to various mobile communication systems.

Claims

1. In the method using the first device, A step of detecting whether the state of a vehicle associated with the first device is a first state; A step of predicting the duration and remaining duration of the first state based on the detection of the first state; and The method includes the step of performing a power saving operation based on at least one control parameter, A method in which at least one control parameter is initially determined based on a first control parameter value determined based on the duration, and is dynamically updated based on a second control parameter value determined based on the remaining duration.

2. In Paragraph 1, A method in which the duration and remaining duration are predicted by an AI (Artificial Intelligence) model trained to predict at least one of the duration and remaining duration based on at least one of the operating state of the vehicle, the location of the vehicle, and a parking pattern associated with the location of the vehicle.

3. In Paragraph 1, A method in which the value of at least one control parameter is dynamically updated based on the output of an AI (Artificial Intelligence) model trained to produce at least one of the first control parameter value and the second control parameter value based on the duration and the remaining duration.

4. In Paragraph 1, A method in which the second control parameter value is dynamically updated based on the ratio between the duration and the remaining duration.

5. In Paragraph 1, A method wherein at least one control parameter comprises a first control parameter for a wake-up period and a second control parameter for an active period.

6. In Paragraph 5, A method in which the values ​​of the first control parameter and the second control parameter are dynamically updated based on the remaining duration and telematics-related scheduling information.

7. In Paragraph 1, A method in which at least one control parameter further includes a trigger condition for event trigger-based wake-up.

8. In Paragraph 7, A step of triggering the event trigger-based wake-up based on the satisfaction of the above trigger condition; and A method further comprising the step of collecting vehicle state information related to the trigger condition based on the fact that the above event trigger-based wake-up is determined to be a false wake-up.

9. In Paragraph 8, A method in which the above trigger condition is dynamically adjusted based on the above collected vehicle status information.

10. In at least one non-transient computer-readable recording medium, Includes instructions that perform operations when executed by at least one processor, The above operations are, Detect whether the state of the vehicle associated with the first device is the first state; Predicting the duration and remaining duration of the first state based on the detection of the first state; and It includes performing a power saving operation based on at least one control parameter, and At least one non-transient computer-readable recording medium, wherein the above at least one control parameter has an initial value determined based on a first control parameter value determined based on the duration, and is dynamically updated based on a second control parameter value determined based on the remaining duration.

11. In the first device, RF (Radio Frequency) transceiver; and It includes a processor connected to the above RF transceiver, and The processor detects whether the state of the vehicle associated with the first device is a first state, predicts the duration and remaining duration of the first state based on the detection of the first state, and performs a power saving operation based on at least one control parameter. A first device wherein at least one control parameter has an initial value determined based on a first control parameter value determined based on the duration, and is dynamically updated based on a second control parameter value determined based on the remaining duration.

12. In Paragraph 11, A first device, wherein the duration and remaining duration are predicted by an AI (Artificial Intelligence) model trained to predict at least one of the duration and remaining duration based on at least one of the operating state of the vehicle, the location of the vehicle, and a parking pattern associated with the location of the vehicle.

13. In a processing device that controls the first device, At least one processor; and It includes at least one memory that stores instructions connected to the above at least one processor and performing operations when executed by the at least one processor, The above operations cause the first device: Detecting whether the state of the vehicle associated with the first device is a first state; Predicting the duration and remaining duration of the first state based on the detection of the first state; and It includes performing a power saving operation based on at least one control parameter, and A processing device wherein at least one control parameter has an initial value determined based on a first control parameter value determined based on the duration, and is dynamically updated based on a second control parameter value determined based on the remaining duration.

14. In a method using a network, A step of receiving state information related to a vehicle in which a first state is detected from a first device; A step of predicting the duration of the first state based on the above state information; and The method includes the step of transmitting power setting information to the first device, the power setting information including at least one control parameter for a power saving operation of the first device. A method comprising at least one control parameter configured such that the power setting information is configured to dynamically adjust the parameter value based on the remaining duration of the first state.

15. In networks, RF (Radio Frequency) transceiver; and It includes a processor connected to the above RF transceiver, and The processor controls the RF transceiver to receive state information related to a vehicle in which a first state is detected from a first device, predicts the duration of the first state based on the state information, and transmits power setting information to the device including at least one control parameter for a power saving operation of the first device. A network comprising at least one control parameter configured such that the power setting information is configured to dynamically adjust the parameter value based on the remaining duration of the first state.

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