WO2023017882A1 - Appareil et procédé pour sélectionner une technologie d'accès radio en tenant compte de l'efficacité de batterie dans un système de communication sans fil - Google Patents

Appareil et procédé pour sélectionner une technologie d'accès radio en tenant compte de l'efficacité de batterie dans un système de communication sans fil Download PDF

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Publication number
WO2023017882A1
WO2023017882A1 PCT/KR2021/010820 KR2021010820W WO2023017882A1 WO 2023017882 A1 WO2023017882 A1 WO 2023017882A1 KR 2021010820 W KR2021010820 W KR 2021010820W WO 2023017882 A1 WO2023017882 A1 WO 2023017882A1
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WIPO (PCT)
Prior art keywords
base station
probability distribution
information
handover
value
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PCT/KR2021/010820
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English (en)
Korean (ko)
Inventor
하업성
오재기
정재훈
박재용
김성진
정성훈
김성준
Original Assignee
엘지전자 주식회사
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Application filed by 엘지전자 주식회사 filed Critical 엘지전자 주식회사
Priority to PCT/KR2021/010820 priority Critical patent/WO2023017882A1/fr
Priority to KR1020237042738A priority patent/KR20240038652A/ko
Publication of WO2023017882A1 publication Critical patent/WO2023017882A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/30—Reselection being triggered by specific parameters by measured or perceived connection quality data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/30—Reselection being triggered by specific parameters by measured or perceived connection quality data
    • H04W36/302—Reselection being triggered by specific parameters by measured or perceived connection quality data due to low signal strength
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/092—Reinforcement learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0058—Transmission of hand-off measurement information, e.g. measurement reports
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/08—Reselecting an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/165—Performing reselection for specific purposes for reducing network power consumption
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the following description relates to a wireless communication system, and relates to an apparatus and method for selecting a radio access technology (RAT) in a wireless communication system.
  • RAT radio access technology
  • a wireless access system is widely deployed to provide various types of communication services such as voice and data.
  • a wireless access system is a multiple access system capable of supporting communication with multiple users by sharing available system resources (bandwidth, transmission power, etc.).
  • Examples of the multiple access system include a code division multiple access (CDMA) system, a frequency division multiple access (FDMA) system, a time division multiple access (TDMA) system, an orthogonal frequency division multiple access (OFDMA) system, and a single carrier frequency (SC-FDMA) system. division multiple access) system.
  • 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
  • eMBB enhanced mobile broadband
  • RAT radio access technology
  • a communication system considering reliability and latency-sensitive services/UE (user equipment) as well as mMTC (massive machine type communications) providing various services anytime and anywhere by connecting multiple devices and objects has been proposed. .
  • Various technical configurations for this have been proposed.
  • the present disclosure may provide an apparatus and method for increasing battery efficiency in a wireless communication system.
  • the present disclosure may provide an apparatus and method for selecting a radio access technology (RAT) capable of increasing battery efficiency in a wireless communication system.
  • RAT radio access technology
  • a method of operating a terminal in a wireless communication system includes receiving measurement configuration information including information related to a probability distribution model for candidate RATs from a first base station, the candidate RAT Transmitting a measurement report including signal quality values for the first base station to the first base station, receiving a handover command message from the first base station, and a second handover command message indicated by the second base station. After accessing the base station, transmitting information related to updating the probability distribution information to a second base station.
  • the measurement report includes a signal quality value for the second base station, and the signal quality value for the second base station may be determined based on the probability distribution model.
  • a method of operating a base station in a wireless communication system includes transmitting measurement configuration information including information related to a probability distribution model for candidate RATs to a terminal, Receiving a measurement report including signal quality values for the measurement report from the terminal, transmitting a handover command message indicating a target base station determined based on the measurement report, and the probability distribution information from the target base station It may include receiving information related to update of .
  • the measurement report includes a signal quality value for the target base station, and the signal quality value for the target base station may be determined based on the probability distribution model.
  • a terminal in a wireless communication system, includes a transceiver and a processor connected to the transceiver.
  • the processor receives, from a first base station, measurement configuration information including information related to a probability distribution model for candidate RATs, and a measurement report including signal quality values for the candidate RATs. ) to the first base station, receiving a handover command message from the first base station, accessing the second base station indicated by the handover command message, and then providing information related to updating the probability distribution information. It can be controlled to transmit to the second base station.
  • the measurement report includes a signal quality value for the second base station, and the signal quality value for the second base station may be determined based on the probability distribution model.
  • a base station in a wireless communication system includes a transceiver and a processor connected to the transceiver.
  • the processor transmits measurement configuration information including information related to a probability distribution model for candidate RATs to the UE, and transmits a measurement report including signal quality values for the candidate RATs.
  • a handover command message received from the terminal and indicating a target base station determined based on the measurement report may be transmitted, and information related to update of the probability distribution information may be received from the target base station.
  • the measurement report includes a signal quality value for the target base station, and the signal quality value for the target base station may be determined based on the probability distribution model.
  • an apparatus includes at least one processor, at least one computer memory connected to the at least one processor and storing instructions that direct operations as executed by the at least one processor, ,
  • the operations include receiving, by the device, measurement configuration information including information related to a probability distribution model for candidate RATs from a first base station, including signal quality values for the candidate RATs. transmitting a measurement report to the first base station, receiving a handover command message from the first base station, accessing the second base station indicated by the handover command message, and then the probability and transmitting information related to updating distribution information to the second base station.
  • the measurement report includes a signal quality value for the second base station, and the signal quality value for the second base station may be determined based on the probability distribution model.
  • a non-transitory computer-readable medium storing at least one instruction (instructions), the at least one instruction executable by a processor (executable) and the at least one instruction comprises: receiving, from a first base station, measurement configuration information including information related to a probability distribution model for candidate RATs, and a signal for the candidate RATs.
  • battery efficiency can be increased in a situation in which a plurality of radio access technologies (RATs) can be utilized.
  • RATs radio access technologies
  • Effects obtainable in the embodiments of the present disclosure are not limited to the above-mentioned effects, and other effects not mentioned are technical fields to which the technical configuration of the present disclosure is applied from the description of the following embodiments of the present disclosure. can be clearly derived and understood by those skilled in the art. That is, unintended effects according to implementing the configuration described in the present disclosure may also be derived by those skilled in the art from the embodiments of the present disclosure.
  • FIG. 1 shows an example of a communication system applicable to the present disclosure.
  • FIG. 2 shows an example of a wireless device applicable to the present disclosure.
  • FIG. 3 illustrates another example of a wireless device applicable to the present disclosure.
  • FIG. 4 shows an example of a portable device applicable to the present disclosure.
  • FIG. 5 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure.
  • AI Artificial Intelligence
  • FIG. 7 illustrates a method of processing a transmission signal applicable to the present disclosure.
  • FIG 8 illustrates an example of a communication structure that can be provided in a 6th generation (6G) system applicable to the present disclosure.
  • FIG. 10 illustrates a THz communication method applicable to the present disclosure.
  • 12A to 12D show examples of updating a probability distribution model applicable to the present disclosure.
  • FIG. 13 illustrates a concept of handover in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 14 illustrates a concept of target RAT selection based on Thompson sampling (TS) in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 15 illustrates examples of probability density functions of a beta distribution usable in a wireless communication system according to an embodiment of the present disclosure.
  • 16 illustrates an example of probability distribution sets defined according to a battery state in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 17 illustrates an example of a procedure for controlling handover in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 18 illustrates an example of a procedure for performing handover in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 19 illustrates an example of a procedure for generating a measurement report in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 20 illustrates an example of a procedure for handover in a wireless communication system according to an embodiment of the present disclosure.
  • 21 illustrates an example of a signal flow for handover in a wireless communication system according to an embodiment of the present disclosure.
  • FIG. 22 illustrates a reward structure based on Thomson sampling in a wireless communication system according to an embodiment of the present disclosure.
  • each component or feature may be considered optional unless explicitly stated otherwise.
  • Each component or feature may be implemented in a form not combined with other components or features.
  • an embodiment of the present disclosure may be configured by combining some elements and/or features. The order of operations described in the embodiments of the present disclosure 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.
  • a base station has meaning as a terminal node of a network that directly communicates with a mobile station.
  • a specific operation described as being performed by a base station in this document may be performed by an upper node of the base station in some cases.
  • the 'base station' is a term such as a fixed station, Node B, eNode B, gNode B, ng-eNB, advanced base station (ABS), or access point. can be replaced by
  • a terminal includes a user equipment (UE), a mobile station (MS), a subscriber station (SS), a mobile subscriber station (MSS), It may be replaced with terms such as mobile terminal or advanced mobile station (AMS).
  • UE user equipment
  • MS mobile station
  • SS subscriber station
  • MSS mobile subscriber station
  • AMS advanced mobile station
  • the transmitting end refers to a fixed and/or mobile node providing data service or voice service
  • the receiving end refers to a fixed and/or mobile node receiving data service or voice service. Therefore, in the case of uplink, the mobile station can be a transmitter and the base station can be a receiver. Similarly, in the case of downlink, the mobile station may be a receiving end and the base station may be a transmitting end.
  • Embodiments of the present disclosure are wireless access systems, such as an IEEE 802.xx system, a 3rd Generation Partnership Project (3GPP) system, a 3GPP Long Term Evolution (LTE) system, a 3GPP 5G (5th generation) NR (New Radio) system, and a 3GPP2 system. It may be supported by at least one disclosed standard document, and in particular, the embodiments of the present disclosure are supported by 3GPP technical specification (TS) 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents It can be.
  • 3GPP technical specification TS 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents It can be.
  • embodiments of the present disclosure may be applied to other wireless access systems, and are not limited to the above-described systems.
  • it may also be applicable to a system applied after the 3GPP 5G NR system, and is not limited to a specific system.
  • 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
  • LTE is 3GPP TS 36.xxx Release 8 or later
  • LTE technology after 3GPP TS 36.xxx Release 10 is referred to as LTE-A
  • xxx Release 13 may be referred to as LTE-A pro.
  • 3GPP NR may mean technology after TS 38.xxx Release 15.
  • 3GPP 6G may mean technology after TS Release 17 and/or Release 18.
  • "xxx" means a standard document detail number.
  • LTE/NR/6G may be collectively referred to as a 3GPP system.
  • FIG. 1 is a diagram illustrating an example of a communication system applied to the present disclosure.
  • a communication system 100 applied to the present disclosure includes a wireless device, a base station, and a network.
  • the wireless device means a device that performs communication using a radio access technology (eg, 5G NR, LTE), and may be referred to as a communication/wireless/5G device.
  • the wireless device includes a robot 100a, a vehicle 100b-1 and 100b-2, an extended reality (XR) device 100c, a hand-held device 100d, and a home appliance. appliance) 100e, Internet of Thing (IoT) device 100f, and artificial intelligence (AI) device/server 100g.
  • a radio access technology eg, 5G NR, LTE
  • XR extended reality
  • IoT Internet of Thing
  • AI artificial intelligence
  • the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing inter-vehicle communication, and the like.
  • the vehicles 100b-1 and 100b-2 may include an unmanned aerial vehicle (UAV) (eg, a drone).
  • UAV unmanned aerial vehicle
  • the XR device 100c includes augmented reality (AR)/virtual reality (VR)/mixed reality (MR) devices, and includes a head-mounted device (HMD), a head-up display (HUD) installed in a vehicle, a television, It may be implemented in the form of smart phones, computers, wearable devices, home appliances, digital signage, vehicles, robots, and the like.
  • the mobile device 100d may include a smart phone, a smart pad, a wearable device (eg, a smart watch, a smart glass), a computer (eg, a laptop computer), and the like.
  • the home appliance 100e may include a TV, a refrigerator, a washing machine, and the like.
  • the IoT device 100f may include a sensor, a smart meter, and the like.
  • the base station 120 and the network 130 may also be implemented as a wireless device, and a specific wireless device 120a may operate as a base station/network node to other wireless devices.
  • the wireless devices 100a to 100f may be connected to the network 130 through the base station 120 .
  • AI technology may be applied to the wireless devices 100a to 100f, and the wireless devices 100a to 100f may be connected to the AI server 100g through the network 130.
  • the network 130 may be configured using a 3G network, a 4G (eg LTE) network, or a 5G (eg NR) network.
  • the wireless devices 100a to 100f may communicate with each other through the base station 120/network 130, but communicate directly without going through the base station 120/network 130 (e.g., sidelink communication). You may.
  • the vehicles 100b-1 and 100b-2 may perform direct communication (eg, vehicle to vehicle (V2V)/vehicle to everything (V2X) communication).
  • the IoT device 100f eg, sensor
  • the IoT device 100f may directly communicate with other IoT devices (eg, sensor) or other wireless devices 100a to 100f.
  • Wireless communication/connection 150a, 150b, and 150c may be performed between the wireless devices 100a to 100f/base station 120 and the base station 120/base station 120.
  • wireless communication/connection includes various types of uplink/downlink communication 150a, sidelink communication 150b (or D2D communication), and inter-base station communication 150c (eg relay, integrated access backhaul (IAB)). This can be done through radio access technology (eg 5G NR).
  • radio access technology eg 5G NR
  • a wireless device and a base station/wireless device, and a base station can transmit/receive radio signals to each other.
  • the wireless communication/connections 150a, 150b, and 150c may transmit/receive signals through various physical channels.
  • various configuration information setting processes for transmitting / receiving radio signals various signal processing processes (eg, channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.) At least a part of a resource allocation process may be performed.
  • FIG. 2 is a diagram illustrating an example of a wireless device applicable to the present disclosure.
  • a first wireless device 200a and a second wireless device 200b may transmit and receive radio signals through various wireless access technologies (eg, LTE and NR).
  • ⁇ the first wireless device 200a, the second wireless device 200b ⁇ denotes the ⁇ wireless device 100x and the base station 120 ⁇ of FIG. 1 and/or the ⁇ wireless device 100x and the wireless device 100x.
  • ⁇ can correspond.
  • the first wireless device 200a includes one or more processors 202a and one or more memories 204a, and may further include one or more transceivers 206a and/or one or more antennas 208a.
  • the processor 202a controls the memory 204a and/or the transceiver 206a and may be configured to implement the descriptions, functions, procedures, suggestions, methods and/or operational flow diagrams disclosed herein.
  • the processor 202a may process information in the memory 204a to generate first information/signal, and transmit a radio signal including the first information/signal through the transceiver 206a.
  • the processor 202a may receive a radio signal including the second information/signal through the transceiver 206a and store information obtained from signal processing of the second information/signal in the memory 204a.
  • the memory 204a may be connected to the processor 202a and may store various information related to the operation of the processor 202a.
  • memory 204a may perform some or all of the processes controlled by processor 202a, or instructions for performing the descriptions, functions, procedures, suggestions, methods, and/or flowcharts of operations disclosed herein. It may store software codes including them.
  • the processor 202a and the memory 204a may be part of a communication modem/circuit/chip designed to implement a wireless communication technology (eg, LTE, NR).
  • the transceiver 206a may be coupled to the processor 202a and may transmit and/or receive wireless signals through one or more antennas 208a.
  • the transceiver 206a may include a transmitter and/or a receiver.
  • the transceiver 206a may be used interchangeably with a radio frequency (RF) unit.
  • RF radio frequency
  • a wireless device may mean a communication modem/circuit/chip.
  • the second wireless device 200b includes one or more processors 202b, one or more memories 204b, and may further include one or more transceivers 206b and/or one or more antennas 208b.
  • the processor 202b controls the memory 204b and/or the transceiver 206b and may be configured to implement the descriptions, functions, procedures, suggestions, methods and/or operational flow diagrams disclosed herein.
  • the processor 202b may process information in the memory 204b to generate third information/signal, and transmit a radio signal including the third information/signal through the transceiver 206b.
  • the processor 202b may receive a radio signal including the fourth information/signal through the transceiver 206b and store information obtained from signal processing of the fourth information/signal in the memory 204b.
  • the memory 204b may be connected to the processor 202b and may store various information related to the operation of the processor 202b.
  • the memory 204b may perform some or all of the processes controlled by the processor 202b, or instructions for performing the descriptions, functions, procedures, suggestions, methods, and/or flowcharts of operations disclosed herein. It may store software codes including them.
  • the processor 202b and the memory 204b may be part of a communication modem/circuit/chip designed to implement a wireless communication technology (eg, LTE, NR).
  • the transceiver 206b may be coupled to the processor 202b and may transmit and/or receive wireless signals through one or more antennas 208b.
  • the transceiver 206b may include a transmitter and/or a receiver.
  • the transceiver 206b may be used interchangeably with an RF unit.
  • a wireless device may mean a communication modem/circuit/chip.
  • one or more protocol layers may be implemented by one or more processors 202a, 202b.
  • the one or more processors 202a and 202b may include one or more layers (eg, PHY (physical), MAC (media access control), RLC (radio link control), PDCP (packet data convergence protocol), RRC (radio resource) control) and functional layers such as service data adaptation protocol (SDAP).
  • One or more processors 202a, 202b may generate one or more protocol data units (PDUs) and/or one or more service data units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and/or operational flow charts disclosed herein.
  • PDUs protocol data units
  • SDUs service data units
  • processors 202a, 202b may generate messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and/or operational flow diagrams disclosed herein.
  • One or more processors 202a, 202b generate PDUs, SDUs, messages, control information, data or signals (eg, baseband signals) containing information according to the functions, procedures, proposals and/or methods disclosed herein , may be provided to one or more transceivers 206a and 206b.
  • One or more processors 202a, 202b may receive signals (eg, baseband signals) from one or more transceivers 206a, 206b, and descriptions, functions, procedures, suggestions, methods, and/or flowcharts of operations disclosed herein PDUs, SDUs, messages, control information, data or information can be obtained according to these.
  • signals eg, baseband signals
  • One or more processors 202a, 202b may be referred to as a controller, microcontroller, microprocessor or microcomputer.
  • One or more processors 202a, 202b may be implemented by hardware, firmware, software, or a combination thereof.
  • ASICs application specific integrated circuits
  • DSPs digital signal processors
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGAs field programmable gate arrays
  • firmware or software may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, and the like.
  • Firmware or software configured to perform the descriptions, functions, procedures, proposals, methods and/or operational flow charts disclosed in this document may be included in one or more processors 202a or 202b or stored in one or more memories 204a or 204b. It can be driven by the above processors 202a and 202b.
  • the descriptions, functions, procedures, suggestions, methods and/or operational flow charts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and/or sets of instructions.
  • One or more memories 204a, 204b may be coupled to one or more processors 202a, 202b and may store various types of data, signals, messages, information, programs, codes, instructions and/or instructions.
  • One or more memories 204a, 204b may include read only memory (ROM), random access memory (RAM), erasable programmable read only memory (EPROM), flash memory, hard drive, registers, cache memory, computer readable storage media, and/or It may consist of a combination of these.
  • One or more memories 204a, 204b may be located internally and/or externally to one or more processors 202a, 202b.
  • one or more memories 204a, 204b may be connected to one or more processors 202a, 202b through various technologies such as wired or wireless connections.
  • One or more transceivers 206a, 206b may transmit user data, control information, radio signals/channels, etc. referred to in the methods and/or operational flow charts of this document to one or more other devices.
  • One or more transceivers 206a, 206b may receive user data, control information, radio signals/channels, etc. referred to in descriptions, functions, procedures, proposals, methods and/or operational flow charts, etc. disclosed herein from one or more other devices. there is.
  • one or more transceivers 206a and 206b may be connected to one or more processors 202a and 202b and transmit and receive radio signals.
  • one or more processors 202a, 202b may control one or more transceivers 206a, 206b to transmit user data, control information, or radio signals to one or more other devices.
  • one or more processors 202a, 202b may control one or more transceivers 206a, 206b to receive user data, control information, or radio signals from one or more other devices.
  • one or more transceivers 206a, 206b may be coupled to one or more antennas 208a, 208b, and one or more transceivers 206a, 206b may be connected to one or more antennas 208a, 208b to achieve the descriptions, functions disclosed in this document.
  • one or more antennas may be a plurality of physical antennas or a plurality of logical antennas (eg, antenna ports).
  • One or more transceivers (206a, 206b) in order to process the received user data, control information, radio signal / channel, etc. using one or more processors (202a, 202b), the received radio signal / channel, etc. in the RF band signal It can be converted into a baseband signal.
  • One or more transceivers 206a and 206b may convert user data, control information, and radio signals/channels processed by one or more processors 202a and 202b from baseband signals to RF band signals.
  • one or more transceivers 206a, 206b may include (analog) oscillators and/or filters.
  • FIG. 3 is a diagram illustrating another example of a wireless device applied to the present disclosure.
  • a wireless device 300 corresponds to the wireless devices 200a and 200b of FIG. 2, and includes various elements, components, units/units, and/or modules. ) can be configured.
  • the wireless device 300 may include a communication unit 310, a control unit 320, a memory unit 330, and an additional element 340.
  • the communication unit may include communication circuitry 312 and transceiver(s) 314 .
  • communication circuitry 312 may include one or more processors 202a, 202b of FIG. 2 and/or one or more memories 204a, 204b.
  • transceiver(s) 314 may include one or more transceivers 206a, 206b of FIG.
  • the control unit 320 is electrically connected to the communication unit 310, the memory unit 330, and the additional element 340 and controls overall operations of the wireless device. For example, the control unit 320 may control electrical/mechanical operations of the wireless device based on programs/codes/commands/information stored in the memory unit 330. In addition, the control unit 320 transmits the information stored in the memory unit 330 to the outside (eg, another communication device) through the communication unit 310 through a wireless/wired interface, or transmits the information stored in the memory unit 330 to the outside (eg, another communication device) through the communication unit 310. Information received through a wireless/wired interface from other communication devices) may be stored in the memory unit 330 .
  • the additional element 340 may be configured in various ways according to the type of wireless device.
  • the additional element 340 may include at least one of a power unit/battery, an input/output unit, a driving unit, and a computing unit.
  • the wireless device 300 may be a robot (FIG. 1, 100a), a vehicle (FIG. 1, 100b-1, 100b-2), an XR device (FIG. 1, 100c), a mobile device (FIG. 1, 100d) ), home appliances (FIG. 1, 100e), IoT devices (FIG.
  • Wireless devices can be mobile or used in a fixed location depending on the use-case/service.
  • various elements, components, units/units, and/or modules in the wireless device 300 may be entirely interconnected through a wired interface or at least partially connected wirelessly through the communication unit 310 .
  • the control unit 320 and the communication unit 310 are connected by wire, and the control unit 320 and the first units (eg, 130 and 140) are connected wirelessly through the communication unit 310.
  • each element, component, unit/unit, and/or module within wireless device 300 may further include one or more elements.
  • the control unit 320 may be composed of one or more processor sets.
  • control unit 320 may include a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphic processing processor, a memory control processor, and the like.
  • memory unit 330 may include RAM, dynamic RAM (DRAM), ROM, flash memory, volatile memory, non-volatile memory, and/or combinations thereof. can be configured.
  • FIG. 4 is a diagram illustrating an example of a portable device applied to the present disclosure.
  • a portable device may include a smart phone, a smart pad, a wearable device (eg, smart watch, smart glasses), and a portable computer (eg, a laptop computer).
  • a mobile device may be referred to as a mobile station (MS), a user terminal (UT), a mobile subscriber station (MSS), a subscriber station (SS), an advanced mobile station (AMS), or a wireless terminal (WT).
  • MS mobile station
  • UT user terminal
  • MSS mobile subscriber station
  • SS subscriber station
  • AMS advanced mobile station
  • WT wireless terminal
  • a portable device 400 includes an antenna unit 408, a communication unit 410, a control unit 420, a memory unit 430, a power supply unit 440a, an interface unit 440b, and an input/output unit 440c. ) may be included.
  • the antenna unit 408 may be configured as part of the communication unit 410 .
  • Blocks 410 to 430/440a to 440c respectively correspond to blocks 310 to 330/340 of FIG. 3 .
  • the communication unit 410 may transmit/receive signals (eg, data, control signals, etc.) with other wireless devices and base stations.
  • the controller 420 may perform various operations by controlling components of the portable device 400 .
  • the controller 420 may include an application processor (AP).
  • the memory unit 430 may store data/parameters/programs/codes/commands necessary for driving the portable device 400 . Also, the memory unit 430 may store input/output data/information.
  • the power supply unit 440a supplies power to the portable device 400 and may include a wired/wireless charging circuit, a battery, and the like.
  • the interface unit 440b may support connection between the mobile device 400 and other external devices.
  • the interface unit 440b may include various ports (eg, audio input/output ports and video input/output ports) for connection with external devices.
  • the input/output unit 440c may receive or output image information/signal, audio information/signal, data, and/or information input from a user.
  • the input/output unit 440c may include a camera, a microphone, a user input unit, a display unit 440d, a speaker, and/or a haptic module.
  • the input/output unit 440c acquires information/signals (eg, touch, text, voice, image, video) input from the user, and the acquired information/signals are stored in the memory unit 430.
  • the communication unit 410 may convert the information/signal stored in the memory into a wireless signal, and directly transmit the converted wireless signal to another wireless device or to a base station.
  • the communication unit 410 may receive a radio signal from another wireless device or base station and then restore the received radio signal to original information/signal. After the restored information/signal is stored in the memory unit 430, it may be output in various forms (eg, text, voice, image, video, or haptic) through the input/output unit 440c.
  • FIG. 5 is a diagram illustrating an example of a vehicle or autonomous vehicle to which the present disclosure applies.
  • a vehicle or an autonomous vehicle may be implemented as a mobile robot, vehicle, train, manned/unmanned aerial vehicle (AV), ship, etc., and is not limited to a vehicle type.
  • AV unmanned aerial vehicle
  • a vehicle or autonomous vehicle 500 includes an antenna unit 508, a communication unit 510, a control unit 520, a driving unit 540a, a power supply unit 540b, a sensor unit 540c, and an autonomous driving unit.
  • a portion 540d may be included.
  • the antenna unit 550 may be configured as a part of the communication unit 510 .
  • Blocks 510/530/540a to 540d respectively correspond to blocks 410/430/440 of FIG. 4 .
  • the communication unit 510 may transmit/receive signals (eg, data, control signals, etc.) with external devices such as other vehicles, base stations (eg, base stations, roadside base units, etc.), servers, and the like.
  • the controller 520 may perform various operations by controlling elements of the vehicle or autonomous vehicle 500 .
  • the controller 520 may include an electronic control unit (ECU).
  • ECU electronice control unit
  • AI devices include TVs, projectors, smartphones, PCs, laptops, digital broadcasting terminals, tablet PCs, wearable devices, set-top boxes (STBs), radios, washing machines, refrigerators, digital signage, robots, vehicles, etc. It may be implemented as a device or a movable device.
  • the AI device 600 includes a communication unit 610, a control unit 620, a memory unit 630, an input/output unit 640a/640b, a running processor unit 640c, and a sensor unit 640d.
  • a communication unit 610 can include Blocks 610 to 630/640a to 640d may respectively correspond to blocks 310 to 330/340 of FIG. 3 .
  • the communication unit 610 communicates wired and wireless signals (eg, sensor information, user data) with external devices such as other AI devices (eg, FIG. 1, 100x, 120, and 140) or AI servers (Fig. input, learning model, control signal, etc.) can be transmitted and received. To this end, the communication unit 610 may transmit information in the memory unit 630 to an external device or transmit a signal received from the external device to the memory unit 630 .
  • external devices eg, sensor information, user data
  • AI devices eg, FIG. 1, 100x, 120, and 140
  • AI servers Fig. input, learning model, control signal, etc.
  • the controller 620 may determine at least one executable operation of the AI device 600 based on information determined or generated using a data analysis algorithm or a machine learning algorithm. And, the controller 620 may perform the determined operation by controlling components of the AI device 600 . For example, the control unit 620 may request, retrieve, receive, or utilize data from the learning processor unit 640c or the memory unit 630, and may perform a predicted operation among at least one feasible operation or one determined to be desirable. Components of the AI device 600 may be controlled to execute an operation. In addition, the control unit 620 collects history information including user feedback on the operation contents or operation of the AI device 600 and stores it in the memory unit 630 or the running processor unit 640c, or the AI server ( 1, 140) can be transmitted to an external device. The collected history information can be used to update the learning model.
  • the memory unit 630 may store data supporting various functions of the AI device 600 .
  • the memory unit 630 may store data obtained from the input unit 640a, data obtained from the communication unit 610, output data of the learning processor unit 640c, and data obtained from the sensing unit 640.
  • the memory unit 630 may store control information and/or software codes required for operation/execution of the controller 620 .
  • the input unit 640a may obtain various types of data from the outside of the AI device 600.
  • the input unit 620 may obtain learning data for model learning and input data to which the learning model is to be applied.
  • the input unit 640a may include a camera, a microphone, and/or a user input unit.
  • the output unit 640b may generate an output related to sight, hearing, or touch.
  • the output unit 640b may include a display unit, a speaker, and/or a haptic module.
  • the sensing unit 640 may obtain at least one of internal information of the AI device 600, surrounding environment information of the AI device 600, and user information by using various sensors.
  • the sensing unit 640 may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, and/or a radar. there is.
  • the learning processor unit 640c may learn a model composed of an artificial neural network using learning data.
  • the running processor unit 640c may perform AI processing together with the running processor unit of the AI server (FIG. 1, 140).
  • the learning processor unit 640c may process information received from an external device through the communication unit 610 and/or information stored in the memory unit 630 .
  • the output value of the learning processor unit 640c may be transmitted to an external device through the communication unit 610 and/or stored in the memory unit 630.
  • the transmitted signal may be processed by a signal processing circuit.
  • the signal processing circuit 700 may include a scrambler 710, a modulator 720, a layer mapper 730, a precoder 740, a resource mapper 750, and a signal generator 760.
  • the operation/function of FIG. 7 may be performed by the processors 202a and 202b and/or the transceivers 206a and 206b of FIG. 2 .
  • blocks 710 to 760 may be implemented in the processors 202a and 202b and/or the transceivers 206a and 206b of FIG. 2 .
  • blocks 710 to 760 may be implemented in the processors 202a and 202b of FIG. 2 .
  • blocks 710 to 750 may be implemented in the processors 202a and 202b of FIG. 2 and block 760 may be implemented in the transceivers 206a and 206b of FIG. 2 , and are not limited to the above-described embodiment.
  • the codeword may be converted into a radio signal through the signal processing circuit 700 of FIG. 7 .
  • a codeword is an encoded bit sequence of an information block.
  • Information blocks may include transport blocks (eg, UL-SCH transport blocks, DL-SCH transport blocks).
  • Radio signals may be transmitted through various physical channels (eg, PUSCH, PDSCH).
  • the codeword may be converted into a scrambled bit sequence by the scrambler 710.
  • a scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of a wireless device.
  • the scrambled bit sequence may be modulated into a modulation symbol sequence by modulator 720.
  • the modulation method may include pi/2-binary phase shift keying (pi/2-BPSK), m-phase shift keying (m-PSK), m-quadrature amplitude modulation (m-QAM), and the like.
  • the complex modulation symbol sequence may be mapped to one or more transport layers by the layer mapper 730. Modulation symbols of each transport layer may be mapped to corresponding antenna port(s) by the precoder 740 (precoding).
  • the output z of the precoder 740 can be obtained by multiplying the output y of the layer mapper 730 by the N*M precoding matrix W.
  • N is the number of antenna ports and M is the number of transport layers.
  • the precoder 740 may perform precoding after transform precoding (eg, discrete fourier transform (DFT)) on complex modulation symbols. Also, the precoder 740 may perform precoding without performing transform precoding.
  • transform precoding eg, discrete fourier transform (DFT)
  • the resource mapper 750 may map modulation symbols of each antenna port to time-frequency resources.
  • the time-frequency resource may include a plurality of symbols (eg, CP-OFDMA symbols and DFT-s-OFDMA symbols) in the time domain and a plurality of subcarriers in the frequency domain.
  • the signal generator 760 generates a radio signal from the mapped modulation symbols, and the generated radio signal can be transmitted to other devices through each antenna.
  • CP cyclic prefix
  • DAC digital-to-analog converter
  • the signal processing process for the received signal in the wireless device may be configured in reverse to the signal processing process 710 to 760 of FIG. 7 .
  • a wireless device eg, 200a and 200b of FIG. 2
  • the received radio signal may be converted into a baseband signal through a signal restorer.
  • the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast fourier transform (FFT) module.
  • ADC analog-to-digital converter
  • FFT fast fourier transform
  • the baseband signal may be restored to a codeword through a resource de-mapper process, a postcoding process, a demodulation process, and a de-scramble process.
  • a signal processing circuit for a received signal may include a signal restorer, a resource demapper, a postcoder, a demodulator, a descrambler, and a decoder.
  • 6G (radio communications) systems are characterized by (i) very high data rates per device, (ii) very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) battery- It aims to lower energy consumption of battery-free IoT devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities.
  • the vision of the 6G system can be four aspects such as “intelligent connectivity”, “deep connectivity”, “holographic connectivity”, and “ubiquitous connectivity”, and the 6G system can satisfy the requirements shown in Table 1 below. That is, Table 1 is a table showing the requirements of the 6G system.
  • the 6G system is enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), mMTC (massive machine type communications), AI integrated communication, tactile Internet (tactile internet), high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion and improved data security ( can have key factors such as enhanced data security.
  • eMBB enhanced mobile broadband
  • URLLC ultra-reliable low latency communications
  • mMTC massive machine type communications
  • AI integrated communication e.g., AI integrated communication
  • tactile Internet tactile internet
  • high throughput high network capacity
  • high energy efficiency high backhaul and access network congestion
  • improved data security can have key factors such as enhanced data security.
  • FIG. 10 is a diagram illustrating an example of a communication structure that can be provided in a 6G system applicable to the present disclosure.
  • a 6G system is expected to have 50 times higher simultaneous wireless communication connectivity than a 5G wireless communication system.
  • URLLC a key feature of 5G, is expected to become a more mainstream technology by providing end-to-end latency of less than 1 ms in 6G communications.
  • the 6G system will have much better volume spectral efficiency, unlike the frequently used area spectral efficiency.
  • 6G systems can provide very long battery life and advanced battery technology for energy harvesting, so mobile devices in 6G systems may not need to be charged separately.
  • AI The most important and newly introduced technology for the 6G system is AI.
  • AI was not involved in the 4G system.
  • 5G systems will support partial or very limited AI.
  • the 6G system will be AI-enabled for full automation.
  • Advances in machine learning will create more intelligent networks for real-time communication in 6G.
  • Introducing AI in communications can simplify and enhance real-time data transmission.
  • AI can use a plethora of analytics to determine how complex target tasks are performed. In other words, AI can increase efficiency and reduce processing delays.
  • AI can also play an important role in machine-to-machine, machine-to-human and human-to-machine communications.
  • AI can be a rapid communication in the brain computer interface (BCI).
  • BCI brain computer interface
  • 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.
  • AI-based physical layer transmission means applying a signal processing and communication mechanism based on an AI driver rather than a traditional communication framework in fundamental signal processing and communication mechanisms. For example, deep learning-based channel coding and decoding, deep learning-based signal estimation and detection, deep learning-based multiple input multiple output (MIMO) mechanism, It may include AI-based resource scheduling and allocation.
  • MIMO multiple input multiple output
  • Machine learning may be used for channel estimation and channel tracking, and may be used for power allocation, interference cancellation, and the like in a downlink (DL) physical layer. Machine learning can also be used for antenna selection, power control, symbol detection, and the like in a MIMO system.
  • DL downlink
  • AI algorithms based on deep learning require a lot of training data to optimize training parameters.
  • a lot of training data is used offline. This is because static training on training data in a specific channel environment may cause a contradiction between dynamic characteristics and diversity of a radio channel.
  • Machine learning refers to a set of actions that train a machine to create a machine that can do tasks that humans can or cannot do.
  • Machine learning requires data and a running model.
  • data learning methods can be largely classified into three types: supervised learning, unsupervised learning, and reinforcement learning.
  • Neural network training is aimed at minimizing errors in the output.
  • Neural network learning repeatedly inputs training data to the neural network, calculates the output of the neural network for the training data and the error of the target, and backpropagates the error of the neural network from the output layer of the neural network to the input layer in a direction to reduce the error. ) to update the weight of each node in the neural network.
  • Supervised learning uses training data in which correct answers are labeled in the learning data, and unsupervised learning may not have correct answers labeled in the learning data. That is, for example, learning data in the case of supervised learning related to data classification may be data in which each learning data is labeled with a category. Labeled training data is input to the neural network, and an error may be calculated by comparing the output (category) of the neural network and the label of the training data. The calculated error is back-propagated in a reverse direction (ie, from the output layer to the input layer) in the neural network, and the connection weight of each node of each layer of the neural network may be updated according to the back-propagation.
  • a reverse direction ie, from the output layer to the input layer
  • the amount of change in the connection weight of each updated node may be determined according to a learning rate.
  • the neural network's computation of input data and backpropagation of errors can constitute a learning cycle (epoch).
  • the learning rate may be applied differently according to the number of iterations of the learning cycle of the neural network. For example, a high learning rate is used in the early stages of neural network learning to increase efficiency by allowing the neural network to quickly achieve a certain level of performance, and a low learning rate can be used in the late stage to increase accuracy.
  • the learning method may vary depending on the characteristics of the data. For example, in a case where the purpose of the receiver is to accurately predict data transmitted by the transmitter in a communication system, it is preferable to perform learning using supervised learning rather than unsupervised learning or reinforcement learning.
  • the learning model corresponds to the human brain, and the most basic linear model can be considered. ) is called
  • the neural network cord used as a learning method is largely divided into deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent boltzmann machine (RNN). and this learning model can be applied.
  • DNN deep neural networks
  • CNN convolutional deep neural networks
  • RNN recurrent boltzmann machine
  • THz communication can be applied in 6G systems.
  • the data transmission rate can be increased by increasing the bandwidth. This can be done using sub-THz communication with wide bandwidth and applying advanced massive MIMO technology.
  • THz waves also known as sub-millimeter radiation
  • THz waves generally represent a frequency band between 0.1 THz and 10 THz with corresponding wavelengths in the range of 0.03 mm-3 mm.
  • the 100 GHz-300 GHz band range (sub THz band) is considered a major part of the THz band for cellular communications. Adding to the sub-THz band mmWave band will increase 6G cellular communications capacity.
  • 300 GHz-3 THz is in the far infrared (IR) frequency band.
  • the 300 GHz-3 THz band is part of the broad band, but is at the border of the wide band, just behind the RF band. Thus, this 300 GHz-3 THz band exhibits similarities to RF.
  • THz communications include (i) widely available bandwidth to support very high data rates, and (ii) high path loss at high frequencies (highly directional antennas are indispensable).
  • the narrow beamwidth produced by the highly directional antenna reduces interference.
  • the small wavelength of the THz signal allows a much larger number of antenna elements to be incorporated into devices and BSs operating in this band. This enables advanced adaptive array technology to overcome range limitations.
  • THz Terahertz
  • FIG. 10 is a diagram illustrating a THz communication method applicable to the present disclosure.
  • THz waves are located between RF (Radio Frequency)/millimeter (mm) and infrared bands, and (i) transmit non-metal/non-polarizable materials better than visible light/infrared rays, and have a shorter wavelength than RF/millimeter waves and have high straightness. Beam focusing may be possible.
  • Multi-arm bandits (MAB) and Thompson sampling (TS)
  • MAB refers to a system in which one candidate can be selected at a time in an environment where a plurality of selectable candidates exist, and the degree of compensation provided in response to the selection is different for each candidate.
  • the selectable candidate may be referred to as an arm.
  • the MAB problem is to find an answer about how to make a selection to maximize the sum of rewards when given a limited number of selection opportunities.
  • the MAB problem can be solved through exploration and exploitation.
  • Use is a method of selecting the best candidate based on existing observations
  • search is a method of selecting new candidates to obtain more observation results. If too few searches are accumulated, choices based on incorrect information may be made. Conversely, if too many searches are conducted, unnecessary opportunity costs may be incurred to obtain more information even though there is sufficient information.
  • utilization and discovery are in a trade-off relationship with each other, and optimizing them is the key to solving the MAB problem.
  • Thomson sampling expresses the probability that a positive reward is given when each arm is selected as a beta distribution.
  • the beta distribution is a probability distribution model represented by two parameters ⁇ and ⁇ .
  • selection of a candidate is performed by randomly sampling values on the x-axis for each of the beta distributions and identifying the candidate corresponding to the largest value.
  • the reward value according to the selection of the corresponding candidate is used to update ⁇ and ⁇ constituting the beta distribution of the corresponding code. For example, a positive result increases ⁇ by 1, and a negative result increases ⁇ by 1.
  • the beta distribution used to express the probability distribution of each candidate in Thomson sampling is defined as in [Equation 1].
  • the beta distribution is a continuous probability distribution defined in the interval [0, 1] by two parameters ⁇ and ⁇ .
  • FIG. 11 shows examples of probability density functions of beta distributions applicable to this disclosure. 11 shows that ( ⁇ , ⁇ ) is (1/3,1), (10,30), (20,20), (1,3), (2,6), (4,4), (2/ 3,2/3), (2,1), and (1,1) beta distributions.
  • ⁇ /( ⁇ + ⁇ ) is (1/3,1), (10,30), (20,20), (1,3), (2,6), (4,4), (2/ 3,2/3), (2,1), and (1,1) beta distributions.
  • a reward distribution of each candidate is estimated using existing data, and a candidate to be given the highest reward is selected according to the estimated distribution.
  • one candidate is selected probabilistically by random sampling based on a beta distribution.
  • ⁇ or ⁇ of the selected candidate is updated based on a result of performing an action according to the selected candidate.
  • the corresponding beta distribution will change to a form that is more concentrated in the center position. It gets lower. If the number of candidates selected is small, the beta distribution will change to a widely distributed form, and the possibility of being selected in the future will arise.
  • FIGS. 12A to 12D Specific examples of updating beta distributions are shown in FIGS. 12A to 12D.
  • 12A to 12D show examples of updating a probability distribution model applicable to the present disclosure.
  • 12A to 12D illustrate changes in three beta distributions (eg, Arm 1, Arm 2, and Arm 3) when selections are made about 1500 times.
  • ( ⁇ , ⁇ ) of the first arm 1, arm 2, and arm 3 are the same as (1,1), (1,1), and (1,1). Since ( ⁇ , ⁇ ) is (1,1), the beta distribution has a uniform distribution with the same probability (eg 1) for all values of x. Since all three arms have the same probability distribution, the search starts with the same probability.
  • ( ⁇ , ⁇ ) of Arm 1, Arm 2, and Arm 3 are (3,2), (2,3), and (2,2).
  • the beta distribution is updated, the probability of each arm being selected is also updated. A clear difference between cancers has not yet been identified.
  • arm 3 since the value selected from the beta distribution of arm 3 is the largest, arm 3 will be selected. The selection of values follows the corresponding beta distribution and is performed by random sampling considering probability.
  • a (2,2) beta distribution such as Arm 3 if random sampling is performed considering the probability, 0.5 with the highest probability will be selected with the highest frequency, but other values other than 0.5 are also less frequent.
  • the y-axis value of 0.5 is about 1.5 and the y-axis value of 0.2 is about 1, so the frequency at which 0.5 is selected through random sampling is 0.2. It can be understood that it is about 1.5 times the frequency of being.
  • ( ⁇ , ⁇ ) of arm 1, arm 2, and arm 3 are (4,3), (2,3), and (5,2).
  • the probability of being selected in the order of arm 3, arm 1, and arm 2 decreases.
  • one value is sampled on the x-axis based on the probability for each of Arm 1, Arm 2, and Arm 3, and since the value selected from the beta distribution of Arm 3 is the largest, Arm 3 will be selected.
  • FIG. 12D after 1496 selections, ( ⁇ , ⁇ ) of Arm 1, Arm 2, and Arm 3 are (33,100), (100,223), and (436,611). Since about 1500 searches have been performed sufficiently, the probability that arm 3 is selected becomes overwhelmingly high.
  • the present disclosure relates to radio access technology (RAT) selection in a wireless communication system, and relates to a technique for selecting a RAT in consideration of battery efficiency by a terminal supporting a plurality of RATs.
  • RAT radio access technology
  • the frequency used for cellular communication will increase and the coverage area of the cell will decrease. Therefore, it is expected that a base station supporting the latest RAT cannot cover all regions in a transitional period when system generations are replaced. In this case, the handover frequency of the wireless device/terminal and the frequency of selecting the RAT during handover may increase.
  • a RAT is selected based on measurement results of signal quality (e.g., received signal strength (RSS), signal to interference noise ratio (SINR), reference signal received power (RSRP), reference signal received quality (RSRQ), etc.) do.
  • signal quality e.g., received signal strength (RSS), signal to interference noise ratio (SINR), reference signal received power (RSRP), reference signal received quality (RSRQ), etc.
  • the UE can select the RAT without considering unnecessary handover and energy efficiency. In this case, energy waste may occur, which may be a serious issue for a terminal with a low battery level.
  • the present disclosure proposes a technique for selecting a RAT in consideration of battery efficiency. Through various embodiments to be described later, the terminal can select a RAT in consideration of battery efficiency and optimize communication performance and power efficiency.
  • Handover in a conventional cellular communication system is performed based on the quality of signals received from base stations.
  • the terminal measures the received signal quality of the serving cell, and continuously camps in the serving cell when the measured signal quality value is greater than or equal to a threshold value.
  • the UE measures the signal quality of the serving cell and the neighbor cell based on the measurement configuration provided from the serving cell, and measures the signal quality of the serving cell and the signal quality of the neighbor cell.
  • the base station of the serving cell that is, the serving base station determines whether to proceed with handover, the target RAT, the target cell, etc.
  • the terminal transmits a confirmation message.
  • battery efficiency is not considered in the RAT selection.
  • the terminal may prefer a RAT capable of providing a better channel environment under the condition that the energy consumed for communication does not exceed a predetermined value.
  • the terminal may prefer a RAT with less energy consumed for communication under a condition in which quality of service (QoS) is maintained. Therefore, according to various embodiments described below, if the RAT is selected based on the AI algorithm considering the battery efficiency of the terminal, QoS maintenance and battery efficiency can be harmonized.
  • FIG. 13 illustrates a concept of handover in a wireless communication system according to an embodiment of the present disclosure.
  • a base station 1320a-1 and a base station 1320a-2 belong to a first system based on a first RAT
  • a base station 1320b-1 and a base station 1320b-2 belong to a second system based on a second RAT. 2 belongs to the system.
  • the base station 1320a-1 is the serving base station of the terminal 1310
  • the terminal 1310 moves.
  • the terminal 1310 includes a cell of the base station 1320a-1, a cell of the base station 1320b-1, a cell of the base station 1320a-1, a cell of the base station 1320a-2, and a cell of the base station 1320b-2. stays sequentially in the cells of In this case, if handover is performed based only on signal quality, the terminal 1310 will perform handovers a total of 4 times, among which 3 handovers between RATs will be performed. Specifically, the terminal 1310 will perform handover twice from the first RAT to the second RAT and once from the second RAT to the first RAT.
  • battery efficiency of the terminal 1310 is considered, handover between RATs may be at least partially excluded.
  • battery efficiency of the UE 1310 is considered when selecting a target RAT. That is, according to various embodiments, the RAT may be selected in consideration of the battery efficiency of the terminal 1310 according to an artificial intelligence algorithm based on whether to maintain QoS and a change in battery consumption rate after handover.
  • Whether to perform inter-RAT handover may be determined by considering at least one of QoS maintenance after handover from base station 1320a-1 to base station 1320b-1 in the past, and change in battery consumption rate.
  • a technology for determining a RAT to be handed over is a RAT selection algorithm that considers battery efficiency of a UE during inter-RAT handover based on a Thomson sampling method that guarantees excellent performance among MAB problem solving methods.
  • MAB is a technique that balances exploitation and exploration in recommendation. Usage recommends the best RAT to the UE, while discovery recommends a new RAT in a balanced way. By applying the MAB technique, a new RAT is appropriately recommended through discovery, and feedback on the selection can be efficiently reflected in the terminal and all base stations.
  • There is a trade-off between use and discovery, and controlling use and discovery may temporarily seem like a loss to the UE, but since several RATs are identified through discovery, it is more efficient overall.
  • FIG. 14 illustrates a concept of target RAT selection based on Thomson sampling in a wireless communication system according to an embodiment of the present disclosure.
  • the MAB-Thomson sampling technique 1420 based on use and search is applied based on data on the plurality of candidate RAT cells 1410-1 to 1410-N, a plurality of candidate RAT cells ( 1410-1 to 1410-N), an optimal RAT cell 1430 may be selected.
  • the data used in the MAB-Thomson sampling technique 1420 is a probability distribution for each RAT.
  • Thomson sampling is an algorithm that estimates the reward distribution of candidate RATs for handover progress based on data observed in the past, and selects a candidate to give the highest reward in the future with high probability based on the estimated distribution. .
  • a reward given to each candidate has a value of 0 or 1 with a probability of p by a Bernoulli trial, and a prior probability of p may follow a beta distribution.
  • the beta distribution is a continuous probability distribution defined on the interval [0, 1] by two parameters ⁇ and ⁇ . When the beta distribution is visualized as a graph, it is shown in FIG. 15 below.
  • 15 illustrates examples of probability density functions of a beta distribution usable in a wireless communication system according to an embodiment of the present disclosure.
  • 15 illustrates beta distributions where ( ⁇ , ⁇ ) are (0.5,0.5), (5,1), (1,3), (2,2), (2,5).
  • ⁇ /( ⁇ + ⁇ ) increases, the center position of the beta distribution approaches 1, and as the value of ⁇ /( ⁇ + ⁇ ) increases, the center position of the beta distribution approaches 0.
  • the reward probability p of the candidate can be estimated to have a distribution of Beta(5, 3).
  • selectable RATs correspond to the beta distributions illustrated in FIG. 15 .
  • the RAT is selected using probability matching based on the given exclusive distributions, i.e., the estimated distribution, which is a method that maximizes the probability of receiving a positive reward for the RAT selected by the base station. .
  • FIG. 16 illustrates an example of probability distribution sets defined according to a battery state in a wireless communication system according to an embodiment of the present disclosure.
  • probability distributions for each RAT may be defined for each battery state.
  • the classification of the battery states 1610-1 to 1610-3 may vary according to various purposes.
  • the battery states may be classified according to at least one of a battery remaining capacity, a battery usage period, and an average power consumption rate of the battery. That is, the system manages probability distributions for a plurality of RATs for each battery state. Accordingly, when handover is required, the system diagnoses the battery state of the terminal to perform handover, and controls to select a target RAT using a probability distribution set corresponding to the diagnosed state.
  • a beta distribution corresponding to each of the candidate RATs may be updated based on evaluation after handover.
  • the terminal may collect information for updating the beta distribution after performing handover.
  • the collected information is used to generate an evaluation index of interest, and includes matters to be considered in determining handover success.
  • the collected information and the evaluation index generated based on the collected information may be collectively referred to as 'evaluation information'.
  • the collected information may relate to battery consumption.
  • a reward value eg, 0 or 1
  • the beta distribution of the target RAT is updated based on the determined reward value. It can be.
  • ⁇ may be increased by 1
  • ⁇ may be increased by 1.
  • Information collected to determine a compensation value and rules for determining a compensation value from the collected information may be designed in various ways according to items to be reflected in handover performance.
  • the compensation value may be determined based on whether to maintain QoS and a change in battery consumption rate.
  • whether to maintain QoS and a change in battery consumption rate may be used as evaluation indicators.
  • the collected information may include service quality indicators (eg, minimum transmission rate, delay time, throughput, etc.), battery consumption rate, and the like.
  • the terminal may observe whether QoS is maintained and a change in battery consumption rate, and determine a compensation value to be reflected in the beta distribution corresponding to the selected candidate RAT based on the observation result.
  • a criterion for determining a specific reward value may be defined in various ways.
  • the compensation value may be determined to be 0. On the other hand, if QoS is maintained after handover and handover is requested again within a predetermined time If not, the compensation value may be determined according to the change in the battery consumption rate. For example, the compensation value may be determined as in [Equation 2] below.
  • R is a compensation value
  • P A is a battery consumption rate before handover
  • P B is a battery consumption rate after handover
  • P T is a threshold value for a change in battery consumption rate.
  • the threshold for the battery consumption rate change is It may be set differently according to the state of the terminal. For example, if the remaining battery power of the terminal exceeds a certain value, a relatively large RSS threshold and a small threshold for the change in battery consumption rate are used, and accordingly, under the condition that the energy consumed in communication does not exceed a certain value A RAT that can secure a good channel environment can be selected. On the other hand, if the remaining battery power of the terminal is below a certain value, a relatively small RSS threshold and a threshold for a large battery consumption rate change are used, and accordingly, an RAT with less energy consumed for communication is selected under the condition that QoS is maintained. It can be.
  • RAT selection and cell selection are described as separate operations, but in some cases, RAT selection may include cell selection. This is because if neighboring cells that can perform handover from one base station support different RATs, selection of one of the neighboring cells includes selection of the RAT. Therefore, in the following description, 'selecting a RAT' may be understood as 'selecting a cell supporting a RAT'. However, when there are multiple cells supporting the same RAT among neighboring cells, RAT selection and cell selection may be separated.
  • 17 illustrates an example of a procedure for controlling handover in a wireless communication system according to an embodiment of the present disclosure. 17 illustrates an operating method of a base station (eg, base station 1320a-1 of FIG. 13) controlling handover.
  • a base station eg, base station 1320a-1 of FIG. 13
  • the base station transmits measurement setting information including information related to probability distribution models for candidate RATs.
  • the probability distribution model may be a probability distribution model based on a beta distribution and may include probability distributions for each candidate RAT.
  • the information related to the probability distribution model is information informing each of the probability distributions for each candidate RAT, and may include two parameters (eg, ⁇ and ⁇ ) constituting a beta distribution per candidate RAT.
  • the base station receives a measurement report including signal quality values for candidate RATs.
  • the candidate RATs include a RAT supported by the base station and other RATs.
  • the measurement report may include signal quality values representing each of the RATs (eg, a signal quality value for a first RAT, a signal quality value for a second RAT, etc.).
  • the signal quality values are signal quality values representing each of the cells (eg, a signal quality value for a first cell supporting the first RAT, a signal quality value for a second cell supporting the first RAT) , a signal quality value for a third cell supporting the second RAT, etc.).
  • the base station performs a handover procedure. Specifically, the base station may transmit a handover command message requesting handover to a target cell supporting the target RAT determined based on the measurement report to the terminal, and receive a message informing of completion of the handover from the base station of the target cell. there is.
  • the base station obtains information related to update of the probability distribution model.
  • the information related to updating the probability distribution model may include information indicating the updated probability distribution model or evaluation information necessary to update the probability distribution model.
  • the evaluation information is information related to a reward value for updating the beta distribution, and may include a reward value or information used to determine the reward value.
  • the information used to determine the compensation value is the QoS value, evaluation of QoS (eg, information on whether or not QoS is maintained), remaining battery capacity, battery consumption rate, battery consumption rate change, and information related to battery consumption rate change. may include at least one of them.
  • information related to update of the probability distribution model may be received through a base station of a target cell during a handover procedure.
  • information related to update of the probability distribution model may be included in a message notifying completion of handover.
  • information related to update of the probability distribution model may be received through a separate message after the handover procedure is completed.
  • the base station may update probability distribution information based on the obtained information.
  • the base station may check beta distribution information (eg, new values of ⁇ and ⁇ ) of the target base station updated by the terminal and apply the information to the stored probability distribution information.
  • the base station may check or determine a compensation value based on the received evaluation information, and update the probability distribution of the target base station among the probability distribution information based on the determined compensation value.
  • the compensation value can be determined as 0 or 1, where 1 means handover success and 0 means handover failure.
  • the updated probability distribution information may be a beta distribution of a neighboring base station handed over by the terminal, that is, a target RAT.
  • the base station may increase one of ⁇ or ⁇ constituting the beta distribution by 1 according to the compensation value.
  • 18 illustrates an example of a procedure for performing handover in a wireless communication system according to an embodiment of the present disclosure. 18 illustrates an operation method of a terminal (eg, terminal 1310 of FIG. 13) performing handover.
  • a terminal eg, terminal 1310 of FIG. 13
  • the UE receives measurement setting information including information related to probability distribution models for candidate RATs.
  • the probability distribution model may be a probability distribution model based on a beta distribution and may include probability distributions for each candidate RAT.
  • the information related to the probability distribution model is information informing each of the probability distributions for each candidate RAT, and may include two parameters (eg, ⁇ and ⁇ ) constituting a beta distribution per candidate RAT.
  • the UE transmits a measurement report including signal quality values for candidate RATs.
  • the candidate RATs include a RAT supported by the base station and other RATs. That is, the terminal may perform measurement on the serving cell and at least one neighboring cell according to the measurement configuration, and transmit a measurement report including a plurality of signal quality values.
  • the measurement report may include signal quality values representing each of the RATs (eg, a signal quality value for a first RAT, a signal quality value for a second RAT, etc.).
  • the signal quality values are signal quality values representing each of the cells (eg, a signal quality value for a first cell supporting the first RAT, a signal quality value for a second cell supporting the first RAT) , a signal quality value for a third cell supporting the second RAT, etc.).
  • step S1805 the terminal performs a handover procedure. Specifically, the UE instructs the target RAT and the target cell from the base station, receives a handover command message requesting handover, and accesses the base station of the target cell. Additionally, the terminal may transmit a message notifying the completion of handover to the base station of the target cell.
  • the terminal transmits information related to update of the probability distribution model.
  • the information related to updating the probability distribution model may include information indicating the updated probability distribution model or evaluation information necessary for updating the probability distribution model.
  • the evaluation information is information related to a reward value for updating the beta distribution, and may include a reward value or information used to determine the reward value.
  • the information used to determine the compensation value is the QoS value, evaluation of QoS (eg, information on whether or not QoS is maintained), remaining battery capacity, battery consumption rate, battery consumption rate change, and information related to battery consumption rate change. may include at least one of them.
  • evaluation information may be received from a base station of a target cell during a handover procedure.
  • the evaluation information may be included in a message notifying completion of handover.
  • the evaluation information may be received through a separate message after the handover procedure is completed.
  • the base station transmits the probability distribution model to the terminal through measurement setting information.
  • the probability distribution model includes probability distribution sets for each battery state (eg, probability distribution sets 1610 - 1 to 1610 - 3 of FIG. 16 ).
  • the base station may transmit measurement setting information including information on all probability distribution sets.
  • the base station may transmit measurement configuration information including information about at least one probability distribution set corresponding to the battery state of the terminal among all probability distribution sets.
  • the base station may obtain information about the battery state of the terminal and select a probability distribution set corresponding to the battery state.
  • the terminal may request measurement configuration upon detecting deterioration of channel quality for the serving cell and may transmit information indicating a battery state together with the request for measurement configuration.
  • the terminal transmits a measurement report including measurement results.
  • the measurement report includes signal quality values for a plurality of cells. At this time, among the signal quality values, a signal quality value related to the RAT selected based on Thomson sampling is reported in a weighted state.
  • An embodiment of generating a measurement report is shown in FIG. 19 below.
  • 19 illustrates an example of a procedure for generating a measurement report in a wireless communication system according to an embodiment of the present disclosure. 19 illustrates an operation method of a terminal (eg, terminal 1310 of FIG. 13) performing handover.
  • a terminal eg, terminal 1310 of FIG. 13
  • the terminal checks a probability distribution set corresponding to the battery state. That is, the terminal checks the battery state (eg, at least one of remaining capacity, use period, and consumption rate) and checks one probability distribution set corresponding to the battery state among a plurality of probability distribution sets.
  • One set of probability distributions includes probability distributions (eg beta distributions) for each candidate RAT.
  • step S1903 the UE samples values from probability distributions for each candidate RAT. That is, the UE samples values from beta distributions of candidate RATs.
  • sampling means an operation of selecting one value from each beta distribution based on a random number and selecting one value in consideration of a probability expressed by a beta distribution curve. For example, in the case of beta(1,1) in FIG. 15, if sampling is performed considering the probability, 0.5 with the highest probability will be selected with the highest frequency, but values other than 0.5 will also be selected with a lower frequency. can
  • the UE applies a weight to the RAT measurement value corresponding to the maximum value among the sampled values.
  • a weight is applied to increase the probability that the selected RAT is selected as the target RAT. That is, the signal quality value for the selected RAT is reported to the base station as a value greater than the measured value.
  • the UE may add a positive offset value (hereinafter referred to as ' ⁇ value') to the measurement value for the selected RAT or multiply it by one or more weight values. If there are a plurality of candidate cells supporting the selected RAT, the UE may apply weights to all signal qualities of the plurality of candidate cells.
  • FIG. 20 illustrates an example of a procedure for handover in a wireless communication system according to an embodiment of the present disclosure.
  • step S2001 the terminal connects to a cellular network.
  • step S2003 the base station transmits measurement configuration information including beta distribution information of candidate RAT cells to the terminal.
  • the base station retains TS models of candidate RAT cells selectable for handover from its own cell, that is, beta distribution information for each terminal state (eg, remaining battery capacity). That is, beta distributions reflecting compensation values determined based on whether or not to maintain QoS after handover of a UE handed over to each RAT cell and a change in battery consumption rate are retained.
  • step S2005 the UE measures RSS for the serving cell and at least one candidate RAT cell.
  • step S2007 the UE selects a RAT considering the battery efficiency of the UE based on the TS model. And, although not shown in FIG. 20, the terminal adds ⁇ to the RSS value for the cell supporting the selected RAT, and then transmits a measurement report including a plurality of RSS values to the base station of the serving cell.
  • step S2009 the base station determines whether to perform handover. The base station of the serving cell determines whether to proceed with handover based on the measurement report, and determines a target RAT and target cell for handover. When it is determined to proceed with handover, the base station transmits a handover command.
  • step S2011 the terminal receives a handover command from the base station of the serving cell and performs handover to the selected target cell.
  • step S2013 the terminal determines the compensation value and updates the TS model based on the compensation value.
  • step S2015 the terminal transmits information related to the updated TS model and handover ACK to the previous serving base station. That is, the terminal transmits a handover confirmation message to the new serving base station, ie, the target base station before handover. Then, the new serving base station transmits a handover confirmation ACK message to the previous serving base station.
  • the TS model is updated by the UE.
  • the TS model may be updated by the base station.
  • the terminal may evaluate whether to maintain QoS and a change in battery consumption rate, and determine a compensation value based on the evaluation result. And, the terminal provides the compensation value to the previous serving base station through the new serving base station, and the previous serving base station can update the TS model.
  • the terminal may provide information related to QoS and battery consumption rate, and the base station may determine a compensation value.
  • 21 illustrates an example of a signal flow for handover in a wireless communication system according to an embodiment of the present disclosure.
  • 21 illustrates a procedure in which a terminal 2110 performs handover from a first base station 2120-1, which is a serving base station, to a second base station 2120-2, which is a neighboring base station.
  • the first base station 2120-1 transmits measurement settings to the terminal 2110.
  • Measurement settings contain information necessary to perform measurements.
  • the measurement setting may include at least one of measurement object information, measurement report configuration information, measurement identification information, measurement item (quantity) information, and measurement gap information.
  • the measurement configuration includes probability distribution model information of candidate RAT cells, that is, beta distribution information.
  • UE 2110 measures RSS values for a serving cell and at least one candidate RAT cell.
  • the terminal 2110 selects a RAT cell having the maximum value among values randomly sampled from a beta distribution of candidate RAT cells corresponding to the current state of the terminal 2110 (eg, remaining battery capacity).
  • UE 2110 adds ⁇ to the RSS measurement value of the selected RAT cell.
  • the terminal 2110 transmits a measurement report to the first base station 2120-1.
  • the measurement report includes RSS values for a serving cell and at least one candidate RAT cell.
  • the RSS value of the selected RAT cell among the RSS values is reported as being increased by ⁇ .
  • step S2111 the first base station 2120-1 determines handover to the second base station 2120-2.
  • the first base station 2120-1 selects the second base station 2120-2 as a target cell for handover based on the measurement report received in step S2109, and performs handover to the second base station 2120-2.
  • decide the first base station 2120-1 transmits a handover request message to the second base station 2120-2.
  • the handover request message includes information about the terminal 2110. Accordingly, the second base station 2120 - 2 determines whether the handover of the terminal 2110 can be accommodated. In this embodiment, handover of the terminal 2110 is accepted.
  • step S2115 the second base station 2120-2 transmits a handover request ACK message to the first base station 2120-1. That is, the second base station 2120 - 2 notifies that the handover of the terminal 2110 can be accepted.
  • step S2117 the first base station 2120-1 transmits a handover command message to the terminal 2110.
  • the handover command message includes information about the target cell, that is, information about the second base station 2120-2.
  • the terminal 2110 transmits a handover confirmation message to the second base station 2120-2.
  • the terminal 2110 may perform a random access procedure for the second base station 2120 - 2 for handover and establish a connection. Thereafter, the terminal 2110 transmits a handover confirmation message through the established connection.
  • the handover confirmation message may include calculated compensation information, that is, a compensation value. That is, terminal 2110 may determine a compensation value based on whether service is maintained after handover and a change in battery consumption rate, and may provide the compensation value to the second base station 2120 - 2 .
  • the second base station 2120-2 transmits a handover confirmation ACK message to the first base station 2120-1.
  • the handover confirmation ACK message informs of the success of handover.
  • the handover confirmation ACK message may include a compensation value received from the terminal 2110. That is, the second base station 2120-2 transfers the compensation value received from the terminal 2110 to the first base station 2120-1.
  • the first base station 2120-1 updates beta distribution information of the TS model. Specifically, the first base station 2120-1 updates the beta distribution of the second base station 2120-2 based on the compensation value. In other words, the first base station 2120-1 may update the parameter ⁇ or parameter ⁇ of the beta distribution of the second base station 2120-2.
  • the UE after the UE measures the RSS values of the serving cell and the candidate cells, applies a weight to the RSS value of the RAT cell selected in the TS model (eg, RSS + ⁇ ), and sends a measurement report to the serving cell send to
  • the ⁇ value may be predefined.
  • the ⁇ value or the range of ⁇ values is set by the base station, and information on the ⁇ value or the range of ⁇ values may be included in a measurement setting including measurement gap information.
  • the terminal when a ⁇ value is provided, the terminal may apply the provided ⁇ value.
  • the terminal when a range of ⁇ values is provided, the terminal may randomly select a ⁇ value within the provided range.
  • the ⁇ value or the range of ⁇ values may be determined based on at least one of a probability value sampled based on a TS model and RSS values reported in the past.
  • the ⁇ value or the range of ⁇ values may be determined based on one of the two modes listed in Table 2 below.
  • mode explanation mode 1 This mode allows a predicted RAT to be selected as a target RAT, when the final RSS value of a cell supporting the predicted RAT is greater than the RSS values of all neighboring cells, and a measurement report triggers (e.g., serving cell RSS value). set the minimum value that can be larger than a certain number) to the range of ⁇ .
  • mode 2 As a mode in which the probability that the RAT predicted by the base station is selected as the target RAT increases, a value or ratio determined for each step according to the TS value of the cell supporting the predicted RAT cell is set in the range of ⁇ .
  • FIG. 22 illustrates a reward structure based on Thomson sampling in a wireless communication system according to an embodiment of the present disclosure. 22 shows a structure in which compensation is fed back based on an evaluation index (eg, whether to maintain QoS or not, battery consumption rate change information) after handover is completed.
  • sampling includes an operation of randomly sampling a value from a beta distribution 2210 of candidate cells. The maximum value is selected by optimization 2220 among the sampled values.
  • the action corresponds to the selected maximum value, that is, after applying a weight to the RSS value for the candidate RAT with the highest battery efficiency (eg, RSS + ⁇ ), including RSS values for a plurality of candidate cells.
  • Observation includes an operation of updating parameters of a beta distribution for compensation based on evaluation 2230 for checking whether QoS is maintained and a change in battery consumption rate after handover is completed. The updated parameters are reflected in the beta distribution 2210.
  • Embodiments of the present disclosure may be applied to various wireless access systems.
  • various wireless access systems there is a 3rd Generation Partnership Project (3GPP) or 3GPP2 system.
  • 3GPP 3rd Generation Partnership Project
  • 3GPP2 3rd Generation Partnership Project2
  • Embodiments of the present disclosure may be applied not only to the various wireless access systems, but also to all technical fields to which the various wireless access systems are applied. Furthermore, the proposed method can be applied to mmWave and THz communication systems using ultra-high frequency bands.
  • embodiments of the present disclosure may be applied to various applications such as free-running vehicles and drones.

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Abstract

La présente divulgation concerne un procédé de fonctionnement d'un terminal pour réaliser un transfert en tenant compte de l'efficacité de la batterie dans un système de communication sans fil, et le procédé de fonctionnement peut comprendre les étapes consistant à : recevoir, en provenance d'une première station de base, des informations de configuration de mesure comprenant des informations relatives à un modèle de distribution de probabilité pour des RAT candidates ; transmettre, à la première station de base, un rapport de mesure comprenant des valeurs de qualité de signal pour les RAT candidates ; recevoir un message de commande de transfert en provenance de la première station de base ; et après avoir accédé à une deuxième station de base indiquée par le message de commande de transfert, transmettre, à la deuxième station de base, des informations relatives à une mise à jour des informations de distribution de probabilité.
PCT/KR2021/010820 2021-08-13 2021-08-13 Appareil et procédé pour sélectionner une technologie d'accès radio en tenant compte de l'efficacité de batterie dans un système de communication sans fil WO2023017882A1 (fr)

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KR1020237042738A KR20240038652A (ko) 2021-08-13 2021-08-13 무선 통신 시스템에서 배터리 효율을 고려하여 무선접속 기술을 선택하기 위한 장치 및 방법

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