Method and apparatus for transmitting and receiving a signal in a wireless communication system

Abstract

A method performed by an environmental Internet of Things (IoT) device according to at least one of the embodiments disclosed in the present disclosure comprises the steps of: receiving a configuration related to at least one first shift gap; transmitting a physical device to reader channel (PDRCH) to a reader based on the at least one first shift gap; and receiving a physical reader to device channel (PRDCH) related to the PDRCH from the reader.

Description

Technical Field

[0001] This disclosure relates to wireless communication systems, and more specifically, to methods and apparatus for transmitting and receiving uplink / downlink signals in wireless communication systems. Background Technology

[0002] 5G mobile communication systems, as the successor to LTE, represent a new state of mobile communication characterized by high performance, low latency, and high availability. 5G NR can utilize all available spectrum resources, from low-frequency bands below 1 GHz, to mid-frequency bands between 1 GHz and 10 GHz, and to high-frequency bands above 24 GHz (such as millimeter waves). 6G systems are being developed based on the fundamental technologies of 5G mobile communication.

[0003] The 6G system aims to achieve: (i) extremely high data rates per device; (ii) a massive number of connected devices; (iii) global connectivity; (iv) ultra-low latency; (v) low-power, battery-free Internet of Things (IoT) devices; (vi) ultra-reliable connectivity; and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be summarized in four aspects: intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity. Summary of the Invention

[0004] Technical issues

[0005] The purpose of this disclosure is to provide a method and apparatus for efficiently performing wireless signal transmission / reception processes. For example, a method and apparatus for efficiently performing collision avoidance between Ambient Internet of Things (A-IoT) devices in A-IoT communication can be provided.

[0006] Those skilled in the art will appreciate that the purposes achievable with this disclosure are not limited to those specifically described above, and that the above and other purposes achievable with this disclosure will become clearer from the following detailed description.

[0007] Technical solution

[0008] According to one aspect of this disclosure, a method performed by an environmental Internet of Things (IoT) device includes: receiving configuration associated with at least one first shift gap; transmitting a Physical Device to Reader Channel (PDRCH) to a reader based on the at least one first shift gap; and receiving a Physical Reader to Device Channel (PRDCH) associated with the PDRCH from the reader.

[0009] According to one aspect of this disclosure, an environmental IoT device in a wireless communication system includes: at least one processor; and at least one computer memory storing instructions that, when executed by the at least one processor, cause the environmental IoT device to perform operations. The operations include: receiving a configuration associated with at least one first shift gap; sending a PDRCH to a reader based on the at least one first shift gap; and receiving a PRDCH associated with the PDRCH from the reader.

[0010] Preferably, the center frequency of the PDRCH is shifted from the reference frequency by at least one first shift gap, including a frequency shift gap. Similarly, the transmission time of the PDRCH is shifted from the reference time by at least one first shift gap, including a time shift gap. More preferably, the frequency shift gap is related to the number of periods of the square wave used for the PDRCH.

[0011] Preferably, based on the number of first shift gaps being two or more, the environmental IoT device selects one of the two or more first shift gaps based on a device index determined as a random value, and applies the selected first shift gap to the PDRCH.

[0012] Preferably, the PRDCH is transmitted from the reader to the environmental IoT device based on a second shift gap corresponding to at least one first shift gap. Alternatively, the PRDCH may include information associated with at least one first shift gap.

[0013] Preferably, the configuration associated with at least one first shift gap is received from a base station (BS) or an intermediate node. In particular, the reader may be at least one of the BS or an intermediate node.

[0014] Furthermore, according to one aspect of this disclosure, a method performed by a reader includes: receiving a PDRCH from an environmental IoT device based on at least one first shift gap, and sending a PDRCH associated with the PDRCH to the environmental IoT device.

[0015] According to one aspect of this disclosure, a reader in a wireless communication system includes: at least one processor; and at least one computer memory storing instructions that, when executed by the at least one processor, cause the reader to perform an operation. The operation includes: receiving a PDRCH from an ambient IoT device based on at least one first shift gap, and sending a PDRCH associated with the PDRCH to the ambient IoT device.

[0016] Preferably, the reader can send a configuration related to at least one first shift gap to the environmental IoT device in advance.

[0017] The foregoing solutions are merely a part of the examples of this disclosure, and those skilled in the art can derive and understand from the following detailed description the various examples in which the technical features of this disclosure are incorporated.

[0018] Beneficial effects

[0019] According to the embodiments, the wireless signal transmission / reception process can be performed efficiently. For example, collision avoidance between Aspect-Oriented Internet of Things (A-IoT) devices can be performed efficiently in A-IoT communication.

[0020] Other advantages of this disclosure will become clearer from the following detailed description. Attached Figure Description

[0021] The accompanying drawings are included to provide an understanding of the present disclosure, illustrating examples of embodiments of the present disclosure and serving, together with the detailed description, to explain embodiments of the present disclosure.

[0022] Figure 1 The illustrations show some examples of flexible network topologies to which this disclosure applies.

[0023] Figure 2 An example of a communication system 100 applied to this disclosure is shown.

[0024] Figure 3 The illustration shows an example of a wireless device applicable to this disclosure.

[0025] Figure 4 The diagram illustrates the communication process between a first node (e.g., UE) and a second node (e.g., BS) in this disclosure.

[0026] Figure 5 An example of a general functional framework for AI / ML models is shown.

[0027] Figure 6 The diagram illustrates the communication process between the first node (e.g., UE) and the second node (BS) to which the AI / ML model is applied.

[0028] Figure 7 The illustration shows an example of an electromagnetic spectrum according to an embodiment of the present disclosure.

[0029] Figure 8 The illustration shows an example of a process for transmitting system information applicable to THz communication as disclosed herein.

[0030] Figure 9 The illustration shows an example of a beam management process applicable to this disclosure.

[0031] Figure 10 The illustration shows an example of sensing operation according to an embodiment of the present disclosure.

[0032] Figure 11 The diagram illustrates time / frequency resources for sensing operations according to this disclosure.

[0033] Figure 12 The diagram illustrates a process related to sensing operation according to this disclosure.

[0034] Figure 13 The illustration shows a topology (e.g., topology 1) in which the BS and the Ambient Internet of Things (A-IoT) device are directly connected according to an embodiment of the present disclosure.

[0035] Figure 14 The diagram illustrates a topology (e.g., topology 2) in which the BS and A-IoT devices are connected via an intermediate node according to an embodiment of the present disclosure.

[0036] Figure 15 The illustration shows a topology supported by auxiliary nodes according to an embodiment of the present disclosure (e.g., topology 3).

[0037] Figure 16 The figure illustrates a topology (e.g., topology 4) in which the UE and the A-IoT device are directly connected according to an embodiment of the present disclosure.

[0038] Figure 17 This is a diagram illustrating the energy harvesting operation of an A-IoT device.

[0039] Figure 18 The diagram illustrates a conflict resolution scenario in A-IoT topology #1.

[0040] Figure 19 The diagram illustrates a conflict resolution scenario in A-IoT topology #2.

[0041] Figure 20 This is a diagram illustrating the signal flow for sending / receiving signals between a reader and an A-IoT device according to this disclosure.

[0042] Figure 21 This is a flowchart illustrating the operations performed by an A-IoT device according to the present disclosure.

[0043] Figure 22 This is a flowchart illustrating the operations performed by the reader according to this disclosure. Detailed Implementation

[0044] In this disclosure, "A or B" can mean "A only", "B only", or "both A and B". In other words, in this disclosure, "A or B" can be interpreted as "A and / or B". For example, in this disclosure, "A, B or C" can mean "A only", "B only", "C only", or "any combination of A, B, and C".

[0045] The forward slash ( / ) or comma used in this disclosure may mean "and / or". For example, "A / B" may mean "A and / or B". Accordingly, "A / B" may mean "A only", "B only", or "both A and B". For example, "A, B, C" may mean "A, B, or C".

[0046] In this disclosure, "at least one of A and B" can mean "only A", "only B" or "both A and B". Furthermore, in this disclosure, the expression "at least one of A or B" or "at least one of A and / or B" can be interpreted as "at least one of A and B".

[0047] Furthermore, in this disclosure, "at least one of A, B and C" can mean "only A", "only B", "only C" or "any combination of A, B and C". Additionally, "at least one of A, B or C" or "at least one of A, B and / or C" can mean "at least one of A, B and C".

[0048] Furthermore, the parentheses used in this disclosure can indicate "for example". Specifically, when expressed as "control information (ABC)", "ABC" can describe an example of "control information". For example, "control information" can also include DEF as another example. In other words, the "control information" of this disclosure is not limited to "ABC", and "ABC" can only describe an example of "control information". Moreover, even when expressed as "control information (i.e., ABC)", "ABC" can also describe an example of "control information".

[0049] Furthermore, the terms "first," "second," etc., used in this disclosure are only used to distinguish one component from another and are not used to limit these components, and unless otherwise specified, do not limit the order, importance, etc., of the components. Therefore, a first component in one embodiment of this disclosure may be referred to as a second component in another embodiment, and similarly, a second component in one embodiment may be referred to as a first component in another embodiment.

[0050] In the following description, “when…”, “if…”, or “in the case of…” can be replaced with “based on”.

[0051] In this disclosure, a technical feature described individually in a figure may be implemented individually or together.

[0052] In this disclosure, a terminal refers to a user-side device (UE, UE) or a consumer-side device, and may also be referred to as a first node that receives or transmits signals to a base station / second node / Integrated Access and Backhaul (IAB) node or Transmit-Receive Point (TRP). A terminal may correspond to a physical node or a logical node. A terminal may correspond to an intermediate point between a user-side endpoint or other endpoints. In communication between two points (including one-to-one, many-to-one, one-to-many, and many-to-many communication) not limited to endpoints, a terminal may correspond to a served node. A terminal may be a node with a fixed location or a node with a non-fixed location (i.e., a mobile node).

[0053] In this disclosure, a base station (BS) refers to a network-side device and may also be referred to as a second node, an IAB node, an x-NodeB (where x may be an abbreviation related to Radio Access Technology (RAT)), or a Transmit-Receive Point (TRP). A base station may correspond to a physical node or a logical node. A base station may correspond to an intermediate point between network-side endpoints or other endpoints. In communication between two points (including one-to-one, many-to-one, one-to-many, and many-to-many communication) not limited to endpoints, a base station may correspond to a serving node. A base station may be a node with a fixed location or a node with a variable location.

[0054] In this disclosure, higher-layer parameters can be configured, pre-configured, or predefined for the UE. For example, the base station can send higher-layer parameters to the UE. For example, the UE can send parameters such as capabilities to the base station as higher-layer parameters. For example, higher-layer parameters can be sent via Radio Resource Control (RRC) signaling or Medium Access Control (MAC) signaling.

[0055] In this disclosure, when information / status / parameters are "configured or pre-configured," it can be interpreted as the information / status / parameters being provided or pre-provided to the UE via predefined signaling (e.g., SIB, MAC, RRC) from the base station. In this disclosure, when information / status / parameters are "defined or pre-defined," it can be interpreted as the information / status / parameters being known or stored in advance by both the base station and the UE without the need for signaling between them.

[0056] The techniques described in this disclosure can be used in various wireless communication systems, such as Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Orthogonal Frequency Division Multiple Access (OFDMA), and Single Carrier Frequency Division Multiple Access (SC-FDMA). CDMA can be implemented using radio technologies such as Universal Terrestrial Radio Access (UTRA) or CDMA2000. TDMA can be implemented using radio technologies such as Global System for Mobile Communications (GSM) / General Packet Radio Service (GPRS) / GSM Evolution Enhanced Data Rate (EDGE). OFDMA can be implemented using radio technologies such as IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Evolved UTRA (E-UTRA), Long Term Evolution (LTE), or 5G New Radio (NR).

[0057] The technologies described in this disclosure can be implemented as 6G wireless technologies and can be applied to various 6G systems. For example, 6G systems can have key elements such as enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), massive machine-type communication (mMTC), artificial intelligence (AI) integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0058] Figure 1 The diagram illustrates an example of a flexible network topology applicable to this disclosure.

[0059] To compensate for incomplete network coverage areas, a more flexible and resilient split radio access network (RAN) topology can be considered. For this purpose, applications such as... Figure 1 The diagram illustrates various nodes such as IAB nodes, repeaters, and RF repeaters, and NTN can also be integrated. For example, an IAB node can correspond to a node that provides wireless backhaul. For example, a repeater can refer to any intermediate point, and in the case of a UE acting as a side-link repeater, it can be collectively referred to as a UE-to-network (U2N) repeater and a UE-to-UE (U2U) repeater. For example, an RF repeater can correspond to a node that performs simple signal amplification and transfer, and in the case of a network-controlled repeater, it can not only perform signal amplification and transfer but also adjust the transmit and receive configurations based on information provided from the network. For example, an NTN node can correspond to a satellite or aircraft that provides NTN coverage that is difficult for terrestrial networks to provide. In addition to these examples, various other intermediate points can be introduced to improve the network topology.

[0060] Reference Figure 1A split RAN can support dividing a base station into a centralized unit (CU) and one or more distributed units (DUs). CUs and DUs can correspond to logical units. A CU can be further divided into a control plane (CP) portion and one or more user plane (UP) portions. Faults in a CU-CP can affect not only CU-UPs but also DUs; therefore, various intermediate points can be introduced to compensate for this.

[0061] Intermediate nodes can correspond to either a UE or a base station based on their relative relationship with other nodes. For example, an IAB node may include a Mobile Terminal (MT) portion and a DU. The MT can connect the IAB node to a donor node. The DU of an IAB node can provide services to other UEs or connect to another IAB node to provide multi-hop radio backhaul to the UE. In other words, an IAB node can correspond to a base station in relation to user-side nodes, and to a UE in relation to network-side nodes.

[0062] In some examples of this disclosure, the description of the UE can be applied equally not only to the user-side endpoint but also to the intermediate point corresponding to the UE in relation to the network-side endpoint. Similarly, in some examples of this disclosure, the description of the base station can be applied equally not only to the network-side endpoint but also to the intermediate point corresponding to the base station in relation to the user-side endpoint. However, where no additional description is provided for the operation of three or more entities in most cases, the communication entities in this disclosure are briefly described by the terms UE and / or base station (or first node and / or second node), wherein the terms UE and / or base station (or first node and / or second node) are to be interpreted as including or replacing any endpoint or intermediate point depending on the relationship with other nodes.

[0063] In other words, in some examples of this disclosure, for the sake of brevity, the subjects of the operation may be referred to as a base station and / or a UE (or a first node and / or a second node). Furthermore, the terms base station and / or UE (or a first node and / or a second node) may be interpreted or replaced as follows: for example, the base station (or the first node) and the UE (or the second node) may correspond to a first endpoint and a second endpoint, respectively; they may correspond to an endpoint and an intermediate point, respectively; they may correspond to an intermediate point and an endpoint, respectively; or they may correspond to a first intermediate point and a second intermediate point, respectively.

[0064] In this disclosure, there may be no intermediate point between the base station and the UE, or there may be one or more intermediate points. When an intermediate point exists, it may correspond to an IAB node, repeater, RF repeater, non-terrestrial network (NTN) node, or a node supporting other functions. The intermediate point may be a node with a fixed location or a node with a variable location.

[0065] Figure 2 The diagram illustrates an example of the structure applicable to the wireless communication system of this disclosure.

[0066] Application of this disclosure Figure 2 The communication system 100 includes a wireless device 110, a network device 120, and a network 130. Here, the wireless device 110 refers to a device that performs communication using radio access technologies (e.g., LTE, LTE-A, LTE-A Pro, NR, 5G, 5G-A, 6G) and may be referred to as a communication / radio / 5G / 6G device. Not limited thereto, the wireless device 110 may include robots 110a, vehicles 110b-1 and 110b-2, extended reality (XR) devices 110c, handheld devices 110d, home appliances 110e, Internet of Things (IoT) devices 110f, and artificial intelligence (AI) devices / servers 110g. For example, vehicles may include vehicles with wireless communication capabilities, autonomous vehicles, or vehicles capable of performing vehicle-to-vehicle communication, and vehicles 110b-1 and 110b-2 may include unmanned aerial vehicles (UAVs) such as drones. XR device 110c may include augmented reality (AR), virtual reality (VR), or mixed reality (MR) devices, and can be implemented in the form of a head-up display (HMD), a head-up display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, or a robot. Handheld device 110d may include a smartphone, a smart tablet, a wearable device (e.g., a smartwatch, smart glasses), or a computer (e.g., a laptop computer). Home appliance 110e may include a television, a refrigerator, or a washing machine. IoT device 110f may include sensors or smart meters. Wireless device 110 may correspond to a UE (or a first node) or an intermediate point. Network device 120 may correspond to a base station (or a second node) or another intermediate point. For example, network device 120 may also be implemented as wireless device 110, and a particular wireless device 120a may act as a network device 120 for another wireless device 110.

[0067] Wireless devices 110a to 110f can be connected to network 130 via network device 120. AI technology can be applied to wireless devices 110a to 110f, and wireless devices 110a to 110f can be connected to AI server 110g via network 130. Network 130 can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, or a 6G network. Wireless devices 110a to 110f can communicate with each other via network device 120 / network 130, but can also communicate directly without going through network device 120 / network 130 (e.g., via sidelink communication). For example, vehicles 110b-1 and 110b-2 can perform direct communication (e.g., vehicle-to-vehicle (V2V) or vehicle-to-everything (V2X) communication). Furthermore, IoT device 110f (e.g., a sensor) can perform direct communication with another IoT device (e.g., another sensor) or with another wireless device 110a to 110f.

[0068] Wireless communication / connections 150a, 150b, and 150c can be established between wireless devices 110a to 110f and network device 120, as well as among network devices 120. Here, the wireless communication / connections can be established using various wireless access technologies, such as uplink / downlink communication 150a, sidelink communication 150b (or D2D communication), and communication between network devices 150c (e.g., relay, integrated access backhaul (IAB)). Through wireless communication / connections 150a, 150b, and 150c, wireless devices can send and receive wireless signals to and from each other, as well as between network devices. For example, wireless communication / connections 150a, 150b, and 150c can send and receive signals through various physical channels. Therefore, based on the various descriptions of this disclosure, at least a portion of various configuration information, various signal processing procedures (e.g., channel coding / decoding, modulation / demodulation, resource mapping / demapping, etc.), and resource allocation procedures can be executed for configuring the process of sending / receiving wireless signals.

[0069] Figure 3 The illustration shows an example of a wireless device applicable to this disclosure.

[0070] Reference Figure 3 The wireless device 200 can transmit / receive radio signals through various wireless access technologies (e.g., LTE, LTE-A, pre-LTE-A, NR, 5G, 5G-A, 6G). The wireless device 200 may include at least one processor 202 and at least one memory 204, and further include at least one transceiver 206 and / or at least one antenna 208.

[0071] Processor 202 may be configured to control memory 204 and / or transceiver 206 and implement the descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document. For example, processor 202 may generate a first information / signal by processing information in memory 204 and then transmit a radio signal including the first information / signal via transceiver 206. Additionally, processor 202 may receive a radio signal including a second information / signal via transceiver 206 and then store information obtained from the signal processing of the second information / signal in memory 204. Memory 204 may be connected to processor 202 and store various information associated with the operation of processor 202. For example, memory 204 may store software code including instructions for implementing some or all of the processes controlled by processor 202 or for implementing the descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document. Here, processor 202 and memory 204 may be part of a communication modem / circuit / chip designed to implement wireless communication technology. Transceiver 206 may be connected to processor 202 and transmit and / or receive radio signals via at least one antenna 208. Transceiver 206 may be a transmitter and / or a receiver. Transceiver 206 may be used interchangeably with a radio frequency (RF) unit. In this disclosure, wireless device may refer to a communication modem / circuit / chip.

[0072] The hardware elements of the wireless device 200 will be described in further detail below. Although not limited thereto, at least one processor 202 may implement at least one protocol layer (e.g., functional layers such as Physical (PHY), Media Access Control (MAC), Radio Link Control (RLC), Packet Data Convergence Protocol (PDCP), Radio Resource Control (RRC), and Service Data Adaptation Protocol (SDAP)). At least one processor 202 may generate at least one Protocol Data Unit (PDU) and / or at least one Service Data Unit (SDU) according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor 202 may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor 202 may generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data, or information according to the functions, procedures, proposals, and / or methods disclosed in this document, and provide such signals to at least one transceiver 206. At least one processor 202 may receive signals (e.g., baseband signals) from at least one transceiver 206 and obtain PDUs, SDUs, messages, control information, data, or information, in accordance with the descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document.

[0073] At least one processor 202 may be referred to as a controller, microcontroller, microprocessor, or microcomputer. At least one processor 202 may be implemented by hardware, firmware, software, or a combination thereof. As an example, at least one specific integrated circuit (ASIC), at least one digital signal processor (DSP), at least one digital signal processing device (DSPD), at least one programmable logic device (PLD), or at least one field-programmable gate array (FPGA) may be included in at least one processor 202. The descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, processes, or functions. Firmware or software configured to execute the descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document may be included in at least one processor 202, or may be stored in at least one memory 204 and executed by at least one processor 202. The descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of code, instructions, and / or instruction sets.

[0074] At least one memory 204 may be connected to at least one processor 202 and store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. At least one memory 204 may be configured as read-only memory (ROM), random access memory (RAM), erasable programmable read-only memory (EPROM), flash memory, hard disk, registers, cache memory, computer-readable storage media, and / or combinations thereof. At least one memory 204 may be located internally and / or externally to at least one processor 202. Furthermore, at least one memory 204 may be connected to at least one processor 202 via various technologies such as wired or wireless connections.

[0075] At least one transceiver 206 can transmit user data, control information, and radio signals / channels mentioned in the methods and / or operation flowcharts of this document to at least one other device. At least one transceiver 206 can receive user data, control information, and radio signals / channels mentioned in the descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document from at least one other device. For example, at least one transceiver 206 can be connected to at least one processor 202 to transmit and receive radio signals. For example, at least one processor 202 can control at least one transceiver 206 to transmit user data, control information, or radio signals to at least one other device. Additionally, at least one processor 202 can control at least one transceiver 206 to receive user data, control information, or radio signals from at least one other device. Furthermore, at least one transceiver 206 can be connected to at least one antenna 208, and at least one transceiver 206 can be configured to transmit and receive user data, control information, and radio signals / channels mentioned in the descriptions, functions, processes, proposals, methods, and / or operation flowcharts disclosed in this document via at least one antenna 208. In this document, at least one antenna may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). At least one transceiver 206 can convert received radio signals / channels from RF band signals to baseband signals to facilitate processing of received user data, control information, and radio signals / channels using at least one processor 202. At least one transceiver 206 can convert user data, control information, and radio signals / channels processed using at least one processor 202 from baseband signals to RF band signals. For this purpose, at least one transceiver 206 may include (analog) oscillators and / or filters.

[0076] Reference Figure 3 The components of the described wireless device may be referred to by other terms in terms of their function. For example, processor 202 may be referred to as a control unit, transceiver 206 as a communication unit, and memory 204 as a storage unit. In some cases, "communication unit" may be used to mean at least a portion of processor 202 and transceiver 206.

[0077] Reference Figure 3 The described wireless device structure can be understood as at least a part of various device structures. For example, Figure 3 The structure of the wireless device shown in the diagram can be compared with that of the reference. Figure 2 At least a portion of the various devices described (e.g., robots 110a, vehicles 110b-1 and 110b-2, XR device 110c, handheld device 110d, home appliance 110e, IoT device 110f, and AI device / server 110g) correspond to each. Furthermore, according to various embodiments, in addition to Figure 3 In addition to the components shown in the diagram, the device may also include other components.

[0078] For example, the device can be a handheld device, such as a smartphone, smart tablet, wearable device (e.g., smartwatch, smart glasses), and handheld computer (e.g., laptop computer, etc.). In this case, the device may further include at least one of the following: a power supply unit that supplies power and includes wired / wireless charging circuitry, a battery, etc.; an interface unit that includes at least one port for connecting to another device (e.g., an audio input / output port, a video input / output port); and an input / output unit for inputting and outputting video information / signals, audio information / signals, data, and / or information input from the user.

[0079] For example, the device can be a mobile device, such as a mobile robot, vehicle, train, manned / unmanned aerial vehicle (AV), and ship. In this case, the device may further include at least one of the following: a drive unit, which includes at least one of the device's engine, electric motor, power transmission system, wheels, brakes, and steering mechanism; a power supply unit, which supplies power and includes wired / wireless charging circuitry, batteries, etc.; a sensor unit, which senses state information, environmental information, and user information of the device or its surroundings; an autopilot unit, which performs functions such as route maintenance, speed control, and destination setting; and a position measurement unit, which obtains the location information of the moving object through a Global Positioning System (GPS) and various sensors.

[0080] For example, the device can be an XR device, such as an HMD, a head-up display (HUD) provided in a vehicle, a television, a smartphone, a wearable device, a home appliance, digital signage, a vehicle, and a robot. In this case, the device may further include at least one of the following: a power supply unit that supplies power and includes wired / wireless charging circuitry, a battery, etc.; an input / output unit that receives control information and data from the outside and outputs the generated XR object; and a sensor unit that senses state information, environmental information, and user information of the device or its surroundings.

[0081] For example, the device may be a robot, which can be classified according to its purpose or field of use, such as industrial use, medical use, domestic use, military use, etc. In this case, the device may further include at least one of the following: a sensor unit that senses state information, environmental information, and user information of the device or its surroundings; and a drive unit that moves the robot joints and performs various other physical operations.

[0082] For example, the device can be an AI device such as a television, projector, smartphone, personal computer, laptop computer, digital broadcasting terminal, tablet PC, wearable device, set-top box (STB), radio, washing machine, refrigerator, digital signage, robot, and vehicle. In this case, the device may also include at least one of the following: an input unit that receives various types of data from the outside; an output unit that generates outputs associated with vision, hearing, or touch; a sensor unit that senses state information, environmental information, and user information of the device or its surroundings; and a training unit that uses learning data to learn a model composed of an artificial neural network.

[0083] Figure 3 The structure of the wireless device illustrated can be understood as part of a UE (or first node), part of an intermediate point, or part of a base station (or second node). When Figure 3 When the illustrated device is a base station (or a second node), it may also include a wired transceiver for fronthaul and / or backhaul communication. However, when fronthaul and / or backhaul communication is based on wireless communication, a wired transceiver may be used. Figure 3 At least one transceiver 206 shown in the figure performs forward and / or backhaul communication, and may not include a wired transceiver.

[0084] Figure 4 The illustration is an example of a communication process applicable to a first node (e.g., a UE) and a second node (e.g., a base station) in this disclosure.

[0085] Figure 4 The second node can support Dynamic Spectrum Sharing (DSS) and can provide connectivity not only to nodes implementing 6G technology but also to nodes implementing pre-6G wireless communication technologies (such as 5G and 4G). In other words, Figure 1 The first node can implement 6G technology, or it can implement pre-6G wireless communication technologies (such as 5G, 4G). In addition, the first node and / or the second node can support not only non-overlapping full-duplex mode, but also full-duplex mode.

[0086] exist Figure 4 For the sake of brevity, it is assumed that the first node and the second node are the UE and the BS, respectively, and the diagram illustrates the operations of UE110 and BS120 in sending and / or receiving data, as well as the operations performed before them. Figure 1 The operation is not limited to the operation between the UE and the base station, and can be interpreted as the operation between the first node and the second node. Furthermore, although... Figure 1 The diagram illustrates direct wireless signal transmission / reception between UE 110 and BS 120, but there may be one or more intermediate points between UE 110 and BS 120, and wireless signals can be transmitted and received through one or more intermediate points.

[0087] Reference Figure 4 In step 101, UE 110 and BS 120 perform synchronization. For example, UE 110 may perform an initial cell search operation. Specifically, UE 110 may detect at least one synchronization signal for base station connection transmitted by BS 120 according to predefined rules. Here, the synchronization signal may include multiple synchronization signals classified according to structure or purpose (e.g., a first synchronization signal (e.g., a primary synchronization signal), a second synchronization signal (e.g., a secondary synchronization signal), etc.). Through this operation, UE 110 can identify the boundaries of units (e.g., frames, subframes, time slots, and / or symbols) configuring radio signal transmission by BS 120, and can obtain information related to BS 120 (e.g., cell identifier).

[0088] In step 103, UE 110 receives system information sent from BS 120. System information is information related to the attributes, characteristics, and / or capabilities of BS 120 that is required for the UE to access BS 120 and use services. It can be categorized according to content (e.g., whether it is necessary for access), transmission structure (e.g., which channel is used, whether it is provided on demand), etc. For example, system information can be divided into first system information (e.g., Master Information Block (MIB), Master System Information) and second system information (e.g., System Information Block (SIB), Secondary System Information). If necessary, UE 110 may send a signal requesting system information before receiving it. However, the request and provision of system information can be performed after the random access procedure described below.

[0089] In step 105, UE 110 and BS 120 perform a random access procedure. UE 110 may send and / or receive at least one message for the random access procedure (e.g., random access preamble, random access response (RAR) message, etc.) based on channel information (e.g., channel location, channel structure, supported preamble structure, etc.) related to the random access procedure of BS 120 obtained through system information. For example, UE 110 may send a first message (e.g., preamble, MSG1) through the channel used for the random access procedure, receive a second message (e.g., RAR message, MSG2), send a third message (e.g., MSG3) to BS 120 including information related to UE 110 (e.g., identification information) using scheduling information included in the second message, and receive a fourth message (e.g., MSG4) for contention resolution and / or connection establishment. In another example, the first and third messages may be sent and received as a single message, or the second and fourth messages may be sent and received as a single message.

[0090] In step 107, UE 110 and BS 120 perform signaling interaction for control information. Here, control information can be defined at various layers, such as layers for controlling connections (e.g., Radio Resource Control (RRC) layer), layers for handling the mapping between logical channels and transport channels (e.g., Medium Access Control (MAC) layer), and layers for handling physical channels (e.g., Physical (PHY) layer). For example, UE 110 and BS 120 can execute at least one of the following signaling: signaling for establishing a connection, signaling for determining communication-related configurations, and signaling for indicating allocated resources.

[0091] In step 109, UE 110 and BS 120 transmit and / or receive data. In other words, UE 110 and BS 120 can process and transmit and / or receive data based on signaling of control information. For example, when transmitting data, UE 110 or BS 120 can perform at least one of channel coding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and resource mapping on the information bits. Conversely, when receiving data, UE 110 or BS 120 can perform at least one of extracting signals from resources, waveform demodulation per antenna, signal arrangement considering layer mapping, constellation demapping, descrambling, and channel decoding.

[0092] The key technologies of 6G systems are described below.

[0093] As the core implementation technology of 6G systems, technologies such as artificial intelligence (AI), terahertz (THz) communication, optical wireless technology, free space light (FSO) backhaul network, massive MIMO technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cellless communication, wireless information and power transfer (WIET), integrated sensing and communication, integrated access and backhaul network, holographic beamforming, big data analysis, and large smart surfaces (LIS) can be adopted.

[0094] Artificial Intelligence

[0095] Introducing artificial intelligence (AI) into communications can simplify and enhance real-time data transmission. AI can determine how to perform complex tasks by using extensive analysis. In other words, AI can improve efficiency and reduce processing latency. Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly by AI. AI can also play an important role in M2M, machine-to-human, and human-to-machine communications. Furthermore, AI can enable high-speed communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, smart structures, smart networks, smart devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0096] The following describes the functional framework used for AI / ML operations.

[0097] To describe AI (or AI / ML) more specifically, the terminology can be defined as follows.

[0098] - Data Acquisition: Data collected from network nodes, management entities, or user units (UEs) to form the basis for AI model training, data analysis, and inference.

[0099] - AI Model: A data-driven algorithm that applies AI technology to generate a set of outputs, including predictive information and / or decision parameters, based on a set of inputs.

[0100] - AI / ML Training: Training AI models by learning functions and patterns that best represent the data and enable inference, either online or offline, to obtain the trained AI / ML model.

[0101] - AI / ML Inference: The process of predicting or deriving decisions based on collected data and the AI ​​model, using a trained AI model.

[0102] The lifecycle management (LCM) process for AI / ML models (i.e., model training, model deployment, model inference, model monitoring, model updates, etc.) can be categorized into function-based LCM and model-based LCM. In function-based LCM, the AI / ML model may not be identifiable within the network, and the network can instruct the activation / deactivation / rollback / switching of AI / ML functions. In model identifier (ID)-based LCM, the AI / ML model can be identified within the network, and the network / UE can activate / deactivate / select / switch the AI / ML model using the model ID.

[0103] Figure 5 An example of a general functional framework for AI / ML models is shown.

[0104] Figure 5 The illustration shows an example of a general functional architecture related to both function-based LCM and model-based LCM. Figure 5 Some functions or parts of the data / information / command flow (i.e., arrows) shown in the diagram may be omitted.

[0105] Reference Figure 5 The general functional framework can be configured to include data acquisition function 10, model training function 20, management function 30, inference function 40, and model storage function 50.

[0106] Data acquisition function 10 provides input data to model training function 20, management function 30, and inference function 40. Data acquisition function 10 can perform data preparation based on raw data, and can provide input data for processing through this data preparation. Examples of raw data may include received or measured data from the UE or other network entities, as well as inference results or outputs from AI / ML models. Data acquisition function 10 can be performed by a single entity (e.g., UE, network node, etc.) or by multiple entities.

[0107] Here, training data 11 refers to the data required as input to the AI / ML model training function 20. Monitoring data 12 refers to the data required as input to the AI / ML model or AI / ML function management function 30. Inference data 13 refers to the data required as input to the AI / ML inference function 30.

[0108] The model training function 20 performs AI / ML model training, validation, and testing, which can generate model performance metrics that can be used as part of the AI / ML model testing process. When necessary, the model training function 20 can perform data preparation (such as data preprocessing and cleaning, formatting, and transformation) based on the training data 11 transmitted from the data acquisition function 10.

[0109] Model 21 for training / updating: If model storage function 50 exists, it is used to transfer the AI / ML model for training, validation and testing to model storage function 50, or to transfer an updated version of the model to model storage function 50.

[0110] Management function 30 supervises the operation of AI / ML models or AI / ML functions. In addition, management function 30 can make decisions based on data received from data acquisition function 10 (i.e., monitoring data 12) and / or data received from inference function 40 (i.e., inference output 41) to ensure appropriate inference operations.

[0111] Management instruction 32 refers to the information required as input to the management inference function 40. This information may include the selection / deactivation / switching of an AI / ML model or AI / ML-based function, and may also include fallback to non-AI / ML operations (i.e., operations independent of the inference process).

[0112] Model transfer / delivery request 33 can be used to request one or more models from model storage function 50.

[0113] Performance feedback / retraining request 31 refers to the information required as input to model training function 20 (e.g., for model retraining or model update purposes).

[0114] The inference function 40 uses the data provided by the data acquisition function 10 (i.e., inference data 13) as input and applies an AI / ML model or AI / ML function to provide output. The inference function 40 can perform data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the inference data 13 transmitted by the data acquisition function 10. If necessary, the inference function 40 can also perform data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) based on the inference data 13 provided by the data acquisition function 10.

[0115] Inference output 41 is data used by management function 30 to monitor the performance of AI / ML models or AI / ML functions. Inference output 41 may include the inference output of the AI / ML model generated by inference function 40, and the details of the inference output may vary depending on the use case.

[0116] Model storage function 50 stores the trained / updated model that can be used to perform inference function 40. Figure 5 The illustrated model storage function 50 can serve as a reference point for protocol termination, model transfer / transmission, and related processes where applicable. Furthermore, model storage function 50 is merely an example and is not intended to limit the actual storage location of AI / ML models; this function can be omitted.

[0117] Model transfer / delivery 51 is used to deliver AI / ML models to inference functions.

[0118] Based on the AI / ML capabilities of multiple nodes, the collaboration level can be defined as follows, and can be modified by combining multiple levels or separating any one level.

[0119] Level 0a) No collaborative framework: AI / ML algorithms are purely based on the implementation method and do not require any modification to the wireless interface.

[0120] Level 0b) This level corresponds to a non-cooperative framework, but involves a modified wireless interface that is adapted to an effectively implemented AI / ML algorithm.

[0121] Level 1 involves node-to-node assistance to improve the AI / ML algorithm on each node. For example, this applies when a particular node receives assistance from another node (for training, adaptation, etc.) and vice versa. At this level, model exchange between network nodes is not required.

[0122] Level 2) enables joint AI / ML operations across multiple nodes. This level requires AI / ML model commands or exchanges between network nodes.

[0123] Figure 5 This is an attached diagram illustrating the overall functional framework of an AI / ML model, and Figure 5The diagram shows that not all functions and / or all data / information / command signals can be executed within a specific node; perhaps only a portion of them can be executed.

[0124] AI / ML models can be classified as one-sided or two-sided models based on whether training and / or inference are performed within a single node or jointly / sequentially across multiple nodes.

[0125] A one-sided model can refer to an AI / ML model inference performed entirely by a single node (e.g., UE or network). Here, training of the AI / ML model can also be performed entirely by a single node. Training and inference of the AI / ML model can be performed by the same node, or they can be performed by different nodes.

[0126] Two-sided models refer to AI / ML models that perform joint inference across multiple nodes (e.g., UE and network). Joint inference means that inference is performed jointly across multiple nodes; for example, the first part of the inference can be performed by the first node, while the remaining part can be performed by the second node. Two-sided models can be classified into several types based on the training methods used to train AI / ML models.

[0127] - Type 1: AI / ML models can be trained on a single node. In this case, joint training can be performed. The trained model can then be distributed to other nodes or entities.

[0128] - Type 2: Joint training of AI / ML models can be performed at multiple nodes or entities (e.g., network and UE). Joint training can refer to model generation (e.g., CSI generation part) and model reconstruction (for CSI compression of sub-use cases) being trained on forward activation and backward gradients within the same loop. Under this type, joint training can include both synchronous training (i.e., performing model generation training and model reconstruction training simultaneously) and sequential training (i.e., performing model reconstruction training after model generation training).

[0129] - The third type: AI / ML models can be trained separately at multiple nodes (e.g., network and UE). Separate training can refer to starting training sequentially at one node and then continuing training at another node. In this case, when the first node executes the AI / ML model first and shares training data with the second node, the second node can use the shared training data to execute the AI / ML model. For example, the training of the CSI generation part can be performed by the UE, while the CSI reconstruction can be performed by the network.

[0130] Figure 6 The diagram illustrates the application of an AI / ML model in the communication process between a first node (e.g., UE) and a second node (e.g., BS).

[0131] In this disclosure described below, even if not specifically mentioned (i.e., not explicitly referenced as such as by / based on / for AI / ML models), the operations presented in this disclosure may be described or interpreted as being based on AI / ML models, such as Figure 6 As shown in the diagram. Figure 6 The illustrations are examples of the operational processes applicable to the AI / ML model-based methods of this disclosure. Furthermore, unless otherwise specifically defined in the description of this disclosure, the AI / ML model may correspond to a one-sided model where inference is performed entirely by a single node, or a two-sided model where joint inference is performed across multiple nodes.

[0132] Step 1: In the description provided below, signaling (e.g., information / data / channel / signaling, etc.) between a specific node (e.g., UE, network, etc.) and another node, even if not explicitly mentioned, can be interpreted as the signaling or set of signaling used in Step 1 to perform operations based on the AI / ML model. For example, such signaling may correspond to... Figure 2 The diagram illustrates training data used for AI / ML model training (i.e., generation and / or reconstruction), or inference data applied to AI / ML model inference, or corresponding feedback to the AI / ML model. Step 1 can be omitted if signaling between nodes is not required before operations based on the AI / ML model in this disclosure. When a one-sided model is used in this disclosure, the one-way / two-way signaling (sets) in this disclosure can correspond to the signaling in step 1. Furthermore, when a two-sided model is used in this disclosure, the one-way / two-way signaling in this disclosure can also correspond to the signaling in step 1, and repeated signaling operations can also correspond to the signaling in step 1.

[0133] For example, in AI / ML model-based beam management (BM), when the base station predicts (i.e., infers) a high-quality beam based on the AI / ML model, the base station can receive quality / strength information of multiple beams from the UE. Similarly, when the UE predicts (i.e., infers) a high-quality beam based on the AI / ML model, the UE can receive multiple beams from the base station.

[0134] Step 2: In the description of this disclosure provided below, an operation (e.g., computation, selection, prediction, etc.) performed at a specific node (e.g., UE, network, etc.) or a joint operation (e.g., computation, selection, prediction, etc.) performed at multiple nodes (e.g., UE, network, etc.), even if not explicitly mentioned, may correspond to the operation of Step 2 based on one or more functions within the AI / ML model functional framework. For example, this may correspond to... Figure 2The diagram illustrates the training (i.e., generation and / or reconstruction) or inference of the AI / ML model. When using a one-sided model, the operation performed by a single node in this disclosure may correspond to the operation in step 2; furthermore, when using a two-sided model, the joint operation performed by multiple nodes in this disclosure may correspond to the operation in step 2.

[0135] For example, in a BM based on an AI / ML model, the base station can use the quality / strength information of multiple beams received from the UE as inference data and predict (i.e., infer) a high-quality beam based on the AI / ML model. Similarly, the UE can measure multiple beams received from the base station, use the measurement results as inference data, and predict (i.e., infer) a high-quality beam based on the AI / ML model.

[0136] Step 3: In the description provided below, the signaling (e.g., information / data / channel / signaling, etc.) between a specific node (e.g., UE, network, etc.) and another node, even if not explicitly mentioned, can be interpreted as the signaling or set of signaling in Step 3 generated based on the operational results of the AI / ML model. For example, this could correspond to... Figure 2 The output obtained from AI / ML model inference is illustrated in the figure. If the operation results based on the AI / ML model in this disclosure do not require signaling between nodes, then step 3 can be omitted. When a one-sided model is used in this disclosure, the one-way / two-way signaling (sets) in this disclosure can correspond to the signaling in step 3. Furthermore, when a two-sided model is used in this disclosure, the one-way / two-way signaling in this disclosure can also correspond to the signaling in step 3, and repeated signaling operations can also correspond to the signaling in step 3.

[0137] For example, in a BM based on an AI / ML model, the base station can send one or more beams predicted by the AI / ML model as candidate beams to the UE, allowing the UE to determine the optimal beam. Furthermore, the UE can report one or more beams predicted by the AI / ML model as candidate beams to the base station, requesting the base station to send candidate beams for determining the optimal beam.

[0138] Terahertz (THz) communication

[0139] Data transmission rates can be increased by expanding bandwidth. This can be achieved by using sub-THz communication with wide bandwidth and applying advanced massive MIMO technology. THz waves, also known as submillimeter-wave radiation, generally refer to the frequency band between 0.1 THz and 10 THz, corresponding to wavelengths of 0.03 mm to 3 mm. The frequency range of 100 GHz–300 GHz (sub-THz band) is considered the main part of the THz band for cellular communication. Adding sub-THz bands to the millimeter-wave band can increase the capacity of 6G cellular communication. Among the defined THz bands, the 300 GHz–3 THz range belongs to the far-infrared (IR) frequency region. The 300 GHz–3 THz range is part of the optical band, but it is located at its boundary, immediately following the RF band. Therefore, the 300 GHz–3 THz range exhibits similarities to the RF band.

[0140] Figure 7 The illustration shows an example of the electromagnetic spectrum applicable to this disclosure. Figure 7 The implementation can be combined with various other implementations. Key characteristics of THz communication include (i) a wide range of available bandwidth supporting extremely high data transmission rates, and (ii) high path loss occurring in the high-frequency band (highly directional antennas are indispensable). The narrow beamwidth generated by highly directional antennas can reduce interference. The short wavelength of THz signals allows for the integration of a much larger number of antenna elements in devices and base stations operating in this band. This enables the use of advanced adaptive array techniques that overcome range limitations.

[0141] In the THz band, transmitting system information (i.e., information related to base station attributes, characteristics, and / or capabilities required for service use, such as MIB and SIB) can be inefficient because beamwidth is narrower in higher frequencies, requiring more frequent beam scans to cover the entire cell area. This inefficiency is even lower when the number of users within a cell is small. Therefore, alternative methods such as... Figure 8 The system information sending process is illustrated in the figure.

[0142] Figure 8 The illustration shows an example of a process for transmitting system information applicable to THz communication as described in this disclosure. Although this example is described with consideration of a THz scenario, it can also be applied to 6G communication environments that do not use THz. Furthermore, Figure 8 The illustrated process can be combined with various embodiments of this disclosure described below. For example, the embodiments described below can be based on... Figure 8 The system information obtained from the process illustrated is used for execution.

[0143] Reference Figure 8In step 501, BS 820 transmits system information for cell #1 through cell #2. That is, BS 820 provides at least two cells, where cell #1 uses the THz frequency band, and cell #2 uses a frequency band other than the THz frequency band. Here, the system information may include at least one piece of information / status / parameter / configuration generated at each of the higher and physical layers. For example, at least one piece of information / status / parameter / configuration generated at a higher layer may include at least one of SFN, SIB1 control information configuration (e.g., SIB1 PDCCH configuration), cell selection / entry related information (e.g., cell prohibition, cell reselection, etc.), and subcarrier spacing; at least one piece of information / status / parameter / configuration generated at the physical layer may include at least one of SFN, half-frame indicator, and SSB index. However, this is only an example; the system information may include information / status / parameter / configuration related to cell #1 and / or cell #2 generated at various types of physical layers and higher layers. Therefore, in one example, cell #1 and cell #2 may have a secondary cell and primary cell relationship.

[0144] In step 503, UE 510 obtains synchronization for cell #1. This synchronization can be obtained by detecting a synchronization signal. Normally, synchronization is obtained before receiving system information; however, since the system information for cell #1 is received via cell #2, synchronization acquisition for cell #1 can be performed after receiving the system information. For example, UE 510 can obtain synchronization based on the system information. But compared to... Figure 8 In contrast, in another example, synchronous fetching can be performed before step 501.

[0145] In step 505, UE 510 transmits a signal for accessing cell #1. For example, this signal may include information for accessing cell #1 (e.g., a random access preamble). The structure of this signal and the resources (e.g., channels) used to transmit it can be determined through system information. Subsequently, in step 507, UE 510 and BS 820 perform the access procedure for cell #1 and initiate communication. In this step, operations corresponding to various embodiments described below can be performed.

[0146] Reference Figure 8 The described procedure can be performed when UE 510 initially accesses cell #1 of BS 820. Alternatively, a similar procedure can be performed when UE 510 is handed over to cell #1 of BS 820. However, in the case of handover, the system information for cell #1 can be received from a cell of another base station, rather than from cell #2 of BS 820.

[0147] Communication in the THz band is expected to encounter significant path loss. To overcome this problem, the UE and base station must use extremely narrow beams. The use of narrow beams means that the UE and base station must perform beam control during beamforming, and the number of beams used becomes very large. Therefore, beam alignment between the base station and UE for transmission and reception takes a considerable amount of time. Furthermore, when beam alignment between the base station and UE is disrupted due to UE movement or mobility, frequent beam realignment is required, which can cause link instability. Therefore, methods such as... Figure 9 The diagram illustrates the beam management process.

[0148] Figure 9 The illustration shows an example of a beam management process applicable to this disclosure. Figure 9 An example of a beam search and / or selection process for THz communication is shown, but this disclosure is not limited to THz environments and can also be applied to 6G communication environments. Furthermore, Figure 9 The processes illustrated herein can be combined with various embodiments of this disclosure described below. Here, the term beam can be interpreted as “spatial (configuration) information,” “spatial domain filter,” “spatial domain transmit filter,” “spatial domain receive filter,” or other terms with equivalent technical meaning that can distinguish a beam (e.g., reference signal, synchronization block (SSB) index, transmit / receive point (TRP), panel, cell, transmit point (TP), base station, or control resource related information, such as control resource set (CORESET) related information).

[0149] Reference Figure 9 In step 601, BS 620 configures resources for beam management. Here, resources may include at least one of time-frequency resources, channels, and spatial resources (e.g., antenna ports). For example, BS 620 may utilize a beam search signal (BSS) for beam searching, which is spatially separated from existing downlink signals / channels. Here, the BSS may be transmitted based on a specific port for beam searching. This specific port may be different from the port used to transmit existing downlink signals / channels (e.g., synchronization signals such as SSB or data channels such as Physical Downlink Shared Channel). The term BSS is defined for ease of explanation, and the technical concept of this embodiment is not limited to the term BSS itself. That is, signals transmitted based on specific ports defined / configured for beam searching are all within the scope of the technical concept of this embodiment.

[0150] In step 603, BS 620 transmits measurement signals using multiple transmit beams. For example, the measurement signals may include at least one of a reference signal and a synchronization signal. In this case, the measurement signals can be transmitted for all beams that need to be measured, and a multi-beam transmission method can be used to transmit them, which can simultaneously form multiple beams to reduce scan time. Here, multi-beam transmission can be performed based on at least one of multiple panels, subarrays, and true time delay (TTD).

[0151] In step 605, UE 610 sends a feedback signal to BS 620. This feedback signal indicates at least one beam selected by UE 610. UE 610 can select at least one preferred beam based on the measurement signal received in step 603. In step 607, UE 610 and BS 620 communicate. At this time, UE 610 and BS 620 can perform communication using the beam selected in step 605. When channel reciprocity is established, the transmit beam of UE 610 can also be determined through steps 603 and 605; therefore, the transmit operation of UE 610 can be performed using the beam selected in step 605. If channel reciprocity is not established, a process including UE 610 transmitting a measurement signal and BS 620 transmitting a feedback signal can be performed in advance to determine the transmit beam of UE 610. In step 607, operations corresponding to various embodiments described below can be performed.

[0152] Sensor and Communication Integration (ISAC)

[0153] Radio sensing is a technology that uses the instantaneous flux velocity, angle, and distance (range) of an object identified by radio frequency identification (RFI) to obtain information related to environmental characteristics and / or the characteristics of objects within that environment. Because RF sensing does not require connecting objects to devices via a network, it can provide object localization services without the need for dedicated equipment. The ability to obtain range, velocity, and angle information from RF signals enables a variety of novel functions, such as object detection, object recognition (e.g., vehicles, humans, animals, drones), high-precision positioning, tracking, and activity recognition. Radio sensing services can provide information to various industries (e.g., drones, smart homes, connected vehicles, factories, railways, public safety, etc.) to support applications such as intrusion detection, assisted driving and navigation, trajectory tracking, collision avoidance, traffic management, and health or traffic monitoring. In some cases, radio sensing can employ non-3GPP sensors (e.g., radar, cameras) to additionally support 3GPP-based sensing. For example, the operation of a radio sensing service, i.e., sensing operation, can depend on the transmission, reflection, and scattering of radio sensing signals. Therefore, radio sensing can provide an opportunity to upgrade existing communication systems from communication networks to radio communication and sensing networks.

[0154] Figure 10 The illustration is applicable to the sensing operation example of this disclosure. Figure 10 The embodiments shown can be combined with various embodiments of this disclosure. Specifically, Figure 10 The diagram illustrates an example of sensing using a sensor receiver and sensor transmitter located in the same location (e.g., monostatic sensing). Figure 10 Figure b illustrates an example of sensing using separate sensor receivers and sensor transmitters (e.g., bistatic sensing).

[0155] For example, in a wireless communication system based on a 6G network according to this disclosure, referring to Figure 10 a. The sensing transmitter and sensing receiver can be configured to be included in a single base station (i.e., the same base station) or a single UE (i.e., the same UE). Conversely, refer to Figure 10 b. The sensing transmitter and sensing receiver can be configured to be included in different base stations, different UEs, or separately in the UE and the base station.

[0156] Based on whether the sensing transmitter and sensing receiver are included in the base station or the UE, the following six sensing modes can be defined: - Mode 1: A mode in which the sensing transmitter and sensing receiver are included in a single base station (e.g., a base station-based sensing mode in a monobase mode). - Mode 2: A mode in which the sensing transmitter is included in a first base station and the sensing receiver is included in a second base station different from the first base station (e.g., a base station-based sensing mode in a bistatic mode). - Mode 3: A mode in which the sensing transmitter is included in the base station and the sensing receiver is included in the UE (e.g., base station to UE sensing mode). - Mode 4: A mode in which the sensing transmitter is included in the UE and the sensing receiver is included in the base station (e.g., UE-to-base station sensing mode). - Mode 5: A mode in which the sensing transmitter and sensing receiver are included in a single UE (e.g., a UE-based sensing mode in monobase mode). - Mode 6: A mode in which the sensing transmitter is included in a first UE and the sensing receiver is included in a second UE that is different from the first UE (e.g., a UE-based sensing mode in a bipolar mode). In the 6G network-based wireless communication system according to this disclosure, one or more of the above six sensing modes can be used independently or in combination.

[0157] Combination Figure 10The illustrated sensing operation involves a sensing transmitter that can transmit sensing signals for sensing one or more objects (and / or their surrounding environment). For example, this sensing signal may correspond to a radio frequency signal defined as transmittable by a base station or UE in a 6G-based wireless communication system according to this disclosure. A sensing receiver can receive signals scattered or reflected by one or more objects (and / or their surrounding environment) from the sensing signals transmitted by the sensing transmitter. At the sensing receiver, sensing data can be derived from the scattered / reflected signals, and sensing results can be generated or obtained through processing the sensing data. Here, the sensing results may include characteristic information (e.g., position, distance, velocity, angle, etc.) of one or more objects (and / or their surrounding environment). The sensing results generated or obtained in this manner can be used for radio sensing services (e.g., object and / or environment detection or tracking) provided by the 6G-based wireless communication system according to this disclosure, or can be provided / disclosed to a trusted third party.

[0158] Additionally, although Figure 10 The sensing operation described in the text is a representative example of operation in a wireless communication system based on a 6G network, but it can also be extended and applied to situations using UEs / base stations / signals based on previous generations (such as 4G, 5G, etc.).

[0159] Furthermore, regarding the radio sensing described in this disclosure, in a 6G network-based wireless communication system according to this disclosure, the time-frequency resources for sensing operations and the time-frequency resources for general communication (e.g., uplink / downlink / sidelink-based communication) can be scheduled / configured separately.

[0160] Figure 11 The illustration is an example of a time-frequency resource applicable to the sensing operation of this disclosure. Figure 11 The implementation methods can be combined with various implementation methods of this disclosure.

[0161] Reference Figure 11 For the above sensing operations (e.g., based on) Figure 10 The time-frequency resources (hereinafter referred to as sensing resources) for sensing operations can be configured / allocated separately from the time-frequency resources (hereinafter referred to as communication resources) used for general communication.

[0162] For example, such as Figure 11 As illustrated, sensing resources can be configured or allocated in the time domain on a per-symbol basis and / or in the frequency domain on a per-resource-block basis. Resources other than those configured or allocated as sensing resources can be used as general communication resources. That is, for the operation of the base station / UE, sensing and communication resources can be configured or allocated based on time-division multiplexing (TDM) and / or frequency-division multiplexing (FDM) schemes. Additionally or alternatively, with Figure 11 Unlike the example shown, sensing resources can be configured or allocated in the time domain based on other units (such as time slots, frames, or absolute time such as milliseconds or microseconds) and / or in the frequency domain based on other units (such as subcarriers, carriers, or absolute frequencies such as megahertz or gigahertz).

[0163] Additionally or alternatively, the configuration / allocation / scheduling of the general communication resources described in this disclosure may need to consider the relationship between such resources and the aforementioned sensing resources. For example, when configuring or allocating general communication resources according to embodiments of this disclosure, these resources may be configured / allocated to perform rate matching or puncturing operations on resource areas corresponding to sensing resources. For example, when scheduling general communication resources according to embodiments of this disclosure, these resources may be scheduled so that they do not overlap with resource areas corresponding to sensing resources. In embodiments of this disclosure, if the resource areas corresponding to general communication resources and sensing resources are configured / allocated / scheduled to overlap, one or both operations may be abandoned, skipped, or postponed based on priority or predefined rules. That is, in embodiments of this disclosure, resources related to general communication (e.g., signal / channel path resources related to data / control based on uplink / downlink / sidelink) are preferably configured / allocated / scheduled to not overlap with the aforementioned sensing resources.

[0164] Additionally, various channel modeling methods can be applied to the radio sensing described in this disclosure. Channel modeling related to sensing can refer to constructing paths for transmitting and / or receiving sensing signals and / or scattered / reflected signals, a process that takes into account the object to be sensed and / or its environment. Since channel modeling can be relevant to the performance and requirements of sensing in a wireless communication system, it can be an important aspect of verifying the feasibility of sensing functionality.

[0165] Sensing-related channels can be categorized into channels between the object (e.g., the target of interest) and the sensing transmitter / receiver, and channels between the object's environment and the sensing transmitter / receiver. Sensing-related channel modeling can be classified based on the sensing mode (e.g., the six modes mentioned above), whether the target of interest is an object or the environment, and / or the sensing scenario. For example, channel modeling for targets in a base station / UE-based monostatic sensing mode, channel modeling for targets in a base station / UE-based bistatic sensing mode, channel modeling for the environment in a base station / UE-based monostatic sensing mode, and channel modeling for the environment in a base station / UE-based bistatic sensing mode can be differentiated and configured respectively. For example, when classifying multiple sensing scenarios, channel modeling can be divided into channel modeling for detection, localization, and tracking scenarios, channel modeling for action recognition, and channel modeling for imaging or environment reconstruction scenarios. Additionally, sensing-related channel modeling can be based on statistical channel modeling techniques and / or deterministic channel modeling techniques. For example, sensing modeling in the 6G network-based wireless communication system of this disclosure can be based on stochastic geometric channel modeling techniques and / or hybrid channel modeling techniques including ray tracing channel modeling. Here, stochastic geometric channel models can be based on various statistical properties of channel conditions. Furthermore, hybrid channel models can be based on both ray tracing and stochastic techniques. In the case of a hybrid approach, channel modeling for objects requiring high accuracy and consistency (e.g., targets of interest) can be performed using ray tracing techniques, while channel modeling for the environment can be performed using stochastic techniques.

[0166] Figure 12 The illustrations are applicable to process examples related to sensing operations in this disclosure. Figure 12 The implementation methods can be combined with various implementation methods of this disclosure.

[0167] For example, in the 6G-based wireless communication system of this disclosure, when the UE participates in sensing operations, the base station may need to identify the UE's capabilities related to the sensing operations. To this end, the UE can be configured to report capability information to the base station, indicating whether it supports sensing operations. Alternatively or additionally, if the UE is predefined by the specification as supporting sensing operations, this process can be omitted. Furthermore, when only the base station participates in the sensing operations, the base station can be configured to report capability information indicating whether it supports sensing operations to the entity that configures or controls its sensing operations (e.g., a higher-level network entity above the base station).

[0168] For example, the base station can interact with the UE via signaling to exchange configuration information related to sensing operations. For instance, the base station can configure or instruct the UE on sensing operation modes (e.g., based on the six modes mentioned above), the entity performing the sensing operation (e.g., a sensing transmitter, a sensing receiver), and the resources for the sensing operation (e.g., [missing information]). Figure 12 This includes information related to the sensing resources shown, the target of the sensing results (e.g., the type of radio sensing service based on a 6G network or a trusted third party), and the channel modeling of the sensing (e.g., the channel between the base station / UE and the object / environment). For example, the base station may be configured / instructed to have such information from a network entity at a higher level / layer than the base station.

[0169] For example, a base station and / or a UE can perform sensing operations based on configuration / instruction information. For instance, a base station and / or a UE acting as a sensing transmitter and / or sensing receiver can perform the following processes: transmitting sensing signals, receiving scattered / reflected signals, deriving sensing data, obtaining sensing results by processing the sensing data, and providing the sensing results. In one example, the sensing results provided through the sensing operations can also be utilized in the operation of the base station / UE described in this disclosure.

[0170] <Environmental IoT in 3GPP Release 18>

[0171] Recently, the Internet of Things for the Environment (A-IoT) has attracted great interest in wireless communication. By reducing the size, complexity, and power consumption of IoT devices and installing and connecting hundreds of billions to trillions of IoT devices, its application in a wide range of fields becomes possible.

[0172] For example, active signal generation and / or backscattering can be considered as one of the communication technologies for enabling low-power operation of A-IoT devices.

[0173] For example, backscattering is a technique widely used in radio frequency identification (RFID) that enables devices to communicate with a network by reflecting incident waves after modulating them with the information to be transmitted. For instance, the device can be powered by the incident RF signal or by stored energy.

[0174] For example, depending on the energy storage and signal generation schemes used, A-IoT devices can be categorized into various device types such as passive, semi-passive, and active. For instance, a passive device does not have an energy storage device (e.g., a capacitor) and can communicate based on backscatter communication. A semi-passive device, for example, has an energy storage device and communicates using backscatter communication with the aid of that energy storage device. An active device, for example, has an energy storage device and can actively generate signals to communicate using active RF components and the stored energy.

[0175] For example, the following three types of IoT devices can be considered in this disclosure. For example, device A may be a device without energy storage and without independent signal generation (e.g., a device supporting backscatter transmission). For example, device B may be a device with energy storage but without independent signal generation (e.g., a device supporting backscatter transmission). In this case, for example, the use of the stored energy may include amplification of the reflected signal. For example, device C may be a device with energy storage and independent signal generation (e.g., a device with active RF components for transmission).

[0176] For example, the following basic topology can be considered to support A-IoT devices in indoor and outdoor scenarios. For example, the basic topology may include direct connections between the BS and the A-IoT device, connections between the BS, intermediate nodes, and the A-IoT device, connections supported by auxiliary nodes, and / or connections between the UE and the A-IoT device. The basic topology presented in this disclosure is merely an example, and the proposals of this disclosure can be extended / applied to other topologies.

[0177] Figure 13 The illustration shows a topology (e.g., topology 1) in which the BS and A-IoT device are directly connected according to an embodiment of the present disclosure. Figure 13 The embodiments described herein can be combined with various embodiments of this disclosure.

[0178] refer to Figure 13 A-IoT devices can communicate directly and bidirectionally with the BS. For example, communication between the BS and the A-IoT device can include A-IoT data and / or signals. For instance, A-IoT data and / or signals can be transmitted or received based on control channels and / or data channels (e.g., shared channels). Figure 13 In some embodiments, the BS sent to the A-IoT device and the BS received from the A-IoT device can be different. For example, in Topology 1, the BS and the A-IoT device in a microcell environment can perform direct communication with each other. For example, the BS can co-locate with a BS equipped with legacy 3GPP technology.

[0179] Figure 14 The diagram illustrates a topology (e.g., topology 2) in which the BS and A-IoT devices are connected via an intermediate node according to an embodiment of the present disclosure. Figure 14 The embodiments described herein can be combined with various embodiments of this disclosure.

[0180] refer to Figure 14A-IoT devices can communicate bidirectionally with intermediate nodes between the device and the BS (Browser / Server). For example, the intermediate node can be a repeater, IAB (Integrated Device Architecture) node, UE (User Equipment), or transponder capable of A-IoT. For example, the intermediate node can transmit A-IoT data and / or signals between the BS and the A-IoT device. For example, A-IoT data and / or signals can be transmitted or received based on control channels and / or data channels (e.g., shared channels). Figure 14 In this embodiment, the intermediate node sent to the A-IoT device and the intermediate node received from the A-IoT device can be different. For example, in Topology 2, the intermediate node can exist between the BS and the A-IoT device in a macrocell environment. For example, the BS can be co-located with a BS equipped with legacy 3GPP technology. For example, the intermediate node may be confined to the UE and located indoors.

[0181] Figure 15 The illustration shows a topology supported by auxiliary nodes according to an embodiment of the present disclosure (e.g., topology 3). Figure 15 The embodiments described herein can be combined with various embodiments of this disclosure.

[0182] refer to Figure 15 (a) can support auxiliary nodes for DL ​​reception. For example, an A-IoT device can send data / signals to a BS, and the A-IoT device can receive data / signals from an auxiliary node. (See reference) Figure 15 (b) can support auxiliary nodes for UL transmission. For example, an A-IoT device can receive data / signals from a BS, and the A-IoT device can transmit data / signals to an auxiliary node. For example, an auxiliary node can be a repeater, IAB node, UE, repeater, etc., capable of A-IoT.

[0183] Figure 16 The figure illustrates a topology (e.g., topology 4) in which the UE and the A-IoT device are directly connected according to an embodiment of the present disclosure. Figure 16 The embodiments described herein can be combined with various embodiments of this disclosure.

[0184] refer to Figure 16 The A-IoT device can communicate bidirectionally with the UE. For example, communication between the UE and the A-IoT device can include A-IoT data and / or signals. For example, A-IoT data and / or signals can be transmitted or received based on control channels and / or data channels (e.g., shared channels).

[0185] For example, A-IoT device transmissions can be performed in a frequency division duplex (FDD) spectrum (e.g., FDD UL spectrum).

[0186] <Environmental IoT in 3GPP Release 19>

[0187] Recently, A-IoT has been discussed in 3GPP Release 19 in order to overcome the limitations of legacy IoT.

[0188] A-IoT devices are classified into Type 1 and Type 2 as follows.

[0189] 1) Type 1: It has a maximum power consumption of about 1uW and performs the transmission to the reader by backscattering a carrier (CW) provided from an external source (e.g., a reader such as a BS or UE, or an independent node).

[0190] 2) Type 2: This type has a maximum power consumption of approximately several hundred uW and performs the transmission to the reader via backscattering from an external source (e.g., a reader such as a BS or UE, or a standalone node) or via internally generated signals. In this disclosure, for convenience, the device type that performs device-to-reader (D2R) transmission via backscattering in device type 2 is defined as type 2a, and the device type that performs D2R transmission via internally generated signals is defined as type 2b.

[0191] Furthermore, in 3GPP Release 19, topology #1, which considers direct communication between the BS and A-IoT device in a macro cell environment, and topology #2, which considers the presence of indirect nodes between the BS and A-IoT device in a macro cell environment, have been studied.

[0192] Furthermore, 3GPP assumes that A-IoT communication occurs in the FDD licensed spectrum of FR1, and in particular, transmissions from A-IoT devices may occur at least in the FDD UL spectrum.

[0193] Figure 17 This is a diagram illustrating the energy harvesting operation of an A-IoT device.

[0194] First, refer to Figure 17 In (b), S1 can be a sleep state, S2 can be an active state, and P1 and P2 can represent the power consumption in S1 and S2, respectively. For example, an active state can refer to a state in which the device consumes power to perform operations such as receiving / transmitting for communication, sensing, etc., and a sleep state can be any state other than an active state.

[0195] also, Figure 17 (a) can represent with Figure 17 (b) The energy state of the corresponding device. (See reference) Figure 17(a) For each device (type / category), the E1 and E2 values ​​may differ, and the device may report information related to the E1 value and / or the E2 value as capability parameters to the reader and / or BS. For example, the E2 value may be defined as the energy value in a fully charged state, and the E1 value may be defined as the minimum energy value required for an active state.

[0196] For example, the transition from S1 to S2 may be possible only if the energy state of the device is E2 or has already reached E2. For example, the transition from S1 to S2 may be possible when the energy state of the device is greater than E1 (i.e., within the range of E1 and E2). Figure 17 The embodiment illustration shows an example of performing a transition from S1 to S2 when the device's energy state value is E2 or has already reached E2.

[0197] A-IoT devices may require CW (Continuous Wave Width) supplied from an external source for backscatter transmission. For example, regardless of the transmission mode (e.g., backscatter transmission or internally generated transmission), CW can be used to supply power to A-IoT devices or as CW for DL ​​(Deep Flow) transmission.

[0198] For example, CW waveforms can be supported in various types. For instance, the type of CW waveform can be a monotone CW waveform or a more complex multitone CW waveform. Because monotone CW uses fewer resources, it may be advantageous compared to multitone CW in terms of interference and tag or reader multiplexing capacity. Conversely, multitone CW has advantages such as the ability to deliver more energy when transmitting CW over DL and ensuring greater coverage from the perspective of a single device.

[0199] Considering the advantages of these different CW waveform types, A-IoT systems can support multiple CW waveform types, and the BS / IN / AN / UE can configure the CW waveform type. For example, one or more CW waveform types supported in the A-IoT communication system can be pre-configured / predefined, and the BS / IN / AN / UE can select one of the supported types to send to the A-IoT device. For example, the BS / IN / AN / UE can configure / guide / instruct the A-IoT device on the selected CW waveform type in the form of a preamble / frame synchronization or a command / message sent as a payload.

[0200] The method proposed in this disclosure can be applied jointly to topologies #1 and #2, and the gNB and UE1, which act as intermediate nodes (IN), are referred to as readers. Furthermore, this disclosure can be extended to cases where the reader receiving the BSS directly generates and transmits CWs, as well as cases where the node transmitting the CW is separate from the reader.

[0201] The A-IoT BS (e.g., reader) used in this disclosure can be a gNB in ​​topology #1 and a specific UE in topology #2. Additionally, the A-IoT device (e.g., tag) used in this disclosure can be interpreted as an A-IoT device in both topology #1 and / or topology #2.

[0202] Collision Avoidance Scheme for A-IoT Communication

[0203] The CW transmitted by the gNB or IN in this disclosure may include a CW for energy harvesting (EH) and a CW for backscattering (BSC). In this disclosure, the CW may be limited to one of these two types or applied jointly to both. For convenience, the CW for EH is referred to as E-CW, and the CW for BSC is referred to as B-CW. Although for convenience only the UE is described as IN, this disclosure can be extended to other types of nodes such as Integrated Access Backhaul (IAB) and Network Control Repeater (NCR).

[0204] Figure 18 The diagram illustrates a conflict resolution scenario in A-IoT topology #1.

[0205] refer to Figure 18 The gNB uses frequency resource #A to transmit CW (for BSC), and its receiving A-IoT device performs BSC to transmit a backscattered signal (BSS). Because the gNB should receive the BSS from the A-IoT device while transmitting CW, self-interference cancellation (SIC) operation may be required.

[0206] In one method for improving SIC performance by suppressing self-interference (SI) during SIC operation of a gNB, the A-IoT device can apply a frequency shift while performing BSC. The magnitude of this frequency shift is conveniently referred to as the F-gap, and as... Figure 18 As shown in the diagram, it can refer to the gap between the center frequencies of the CW and BSS.

[0207] In an example of a method for implementing the F-gap by an A-IoT device, Miller subcarrier coding technology used in RFID standards (e.g., EPCglobal Class 1 Generation 2 UHF RFID standard) can be applied. In another example, where a device type 2 (i.e., type 2b) performs UL transmission via an internally generated signal, it can directly generate a signal with a center frequency of CW+F-gap. In this case, dynamically changing the size of the F-gap in the A-IoT device implementation may not be straightforward compared to applying the F-gap based on an external CW. Furthermore, when multiple A-IoT devices transmit BSS in response to a CW sent by a gNB, collisions may occur if the F-gap is the same.

[0208] Therefore, this disclosure aims to propose an F-gap generation method to maximize the SiC performance of the gNB and reduce conflicts between A-IoT devices. Furthermore, since generating a time axis gap (i.e., referred to as a T-gap (Tgap)) in addition to a frequency axis gap such as a frequency shift may benefit the SiC performance of the gNB and mitigate conflicts between A-IoT devices, a T-gap generation method for the same purpose is also proposed.

[0209] Figure 19 The diagram illustrates a scenario where SIC operation is required in A-IoT topology #2.

[0210] refer to Figure 19 UE1, acting as IN, uses frequency resource #A to transmit CW (for BSC), and the A-IoT device receiving CW performs BSC to transmit BSS. Because UE1 should receive BSS from the A-IoT device that is simultaneously transmitting CW, SIC operation may be required.

[0211] In one method for improving SIC performance by suppressing SI during SIC operation of UE1, the A-IoT device can apply a frequency shift while performing BSC. The magnitude of the frequency shift is called the F-gap, meaning that... Figure 19 The diagram shows the gap between the center frequencies of the CW and BSS.

[0212] In an example of a method for implementing the F-gap by A-IoT devices, Miller subcarrier coding technology used in RFID standards (e.g., EPCglobal Class 1 Generation 2 UHF RFID standard) can be applied. In another example, in the case where device type 2 performs UL transmission via an internally generated signal, it can directly generate a signal with a center frequency of CW+F-gap. Furthermore, when multiple A-IoT devices transmit BSS in response to a CW sent by UE1, a collision may occur if the F-gap is the same.

[0213] Therefore, this disclosure aims to propose an F-gap generation method to maximize the SIC performance of UE1 and reduce conflicts between A-IoT devices. Furthermore, since generating time-axis gaps (i.e., referred to as T-gap) in addition to frequency-axis gaps such as frequency shifts may benefit the SIC performance of UE1 and mitigate conflicts between A-IoT devices, a T-gap generation method for the same purpose is also proposed.

[0214] For ease of description, the F-gap and T-gap applied to the signals sent from the A-IoT device to the reader are referred to as F-gap_T and T-gap_T, respectively. Additionally, the F-gap and T-gap applied to the signals sent from the reader to the A-IoT device are referred to as F-gap_R and T-gap_R, respectively.

[0215] <Proposal 1: Methods for signal transmission in A-IoT devices and signal reception in readers>

[0216] First, a method for transmitting signals using F-gap_T and / or T-gap_T by an A-IoT device (or group of A-IoT devices) will be described.

[0217] In determining the size of F-gap_T and / or T-gap_T, the A-IoT device may consider one or more of the exemplary parameters in 1) to 7) below, and the determining factor for determining the size of F-gap_T and / or T-gap_T based thereon may be predetermined / predefined or may be configured / indicated by the reader.

[0218] 1) A-IoT Device Index; 2) Subframe index; 3) Time slot index; 4) CP-OFDM symbol index for NR systems; 5) Symbol index for A-IoT communication; 6) A-IoT device type (e.g., different sizes of F-gap_T and / or T-gap_T can be applied according to type 1, type 2a, or type 2b, and the size values ​​can be predetermined / predefined or configured / indicated by the reader); and 7) Capabilities regarding the (maximum) size of F-gap_T and / or T-gap_T for A-IoT devices.

[0219] Specifically, the size of the F-gap_T that can be defined / configured / indicated can be different for each device type. For example, the size of the F-gap_T that can be defined / configured / indicated for device type 2b can be larger than the size of the F-gap_T that can be defined / configured / indicated for device types 1 / 2a. Alternatively, the size of the F-gap_T applied to device type 2b can be predefined or configured / indicated by the reader to be larger than the size of the F-gap_T applied to device types 1 / 2a. This method can achieve efficient coexistence by supporting FDM between different device types.

[0220] In alternative schemes for applying FDM between device types, the frequency bands used for R2D / D2R communication can be different for each device type. For example, coexistence via FDM can be achieved by configuring the frequency bands for R2D / D2R communication for device type 2b and R2D / D2R communication for device types 1 / 2a differently (i.e., separately).

[0221] Alternatively, the TDM approach can be considered a way to ensure effective coexistence between different device types.

[0222] In one approach, R2D / D2R communication periods, such as session and / or inventory rounds, may be configured / operated differently depending on the device type. For example, R2D / D2R communication periods for device type 1 / 2a and R2D / D2R communication periods for device type 2b may be configured / operated differently.

[0223] In another approach, it is possible to configure / instruct only specific device types to respond via R2D messages such as preambles, midambles, postambles, physical reader-to-device channels (PRDCH), query commands, or paging messages. For example, when a specific device type (e.g., type 1 and / or type 2a and / or type 2b) is indicated / configured via a specific sequence or field in an R2D message, only the device type can send a response to the R2D message.

[0224] For example, a preamble may consist of a start indicator portion and / or a clock acquisition portion. The start indicator portion can be used as a signal to indicate the start of a PRDCH, and the clock acquisition portion can be used to perform time / frequency synchronization to receive subsequent PRDCHs.

[0225] A middle guide can be inserted in the middle of the PDCH to assist in time / frequency synchronization during PDCH reception. Additionally, a end guide can be inserted at the end of the PRDCH to assist in time / frequency synchronization during PRDCH reception or to signal the end of the PRDCH. In another approach, the size of the T-gap_T can be defined / configured / indicated for each device type. For example, the size of the T-gap_T defined / configured / indicated for device type 2b can be greater than (or less than) the size of the T-gap_T defined / configured / indicated for device types 1 / 2a. Alternatively, the size of the T-gap_T applied to device type 2b can be predetermined or configured / indicated by the reader to be greater than (or less than) the size of the T-gap_T applied to device types 1 / 2a.

[0226] When there are A-IoT devices that can apply F-gap (hereinafter, device category 1) and A-IoT devices that cannot apply F-gap (hereinafter, device category 2), FDM and / or TDM methods can also be applied only when these two device categories coexist.

[0227] Specifically, different R2D / D2R communication periods (e.g., session and / or inventory rounds) can be configured / operated according to the device category. For example, different R2D / D2R communication periods can be configured / operated for device category 1 and device category 2.

[0228] In another approach, it is possible to configure / indicate only a specific device type to respond via R2D messages (e.g., preamble, introductory, post-introductory, PRDCH, query command, or paging message). For example, when a specific device category (e.g., device category 1 and / or device category 2) is indicated / configured via a specific sequence or field in an R2D message, only the device category can send a response to the R2D message.

[0229] In another approach, the size of the T-gap_T that can be defined / configured / indicated can be different for each device category. For example, the size of the T-gap_T that can be defined / configured / indicated for device category 2 can be greater than (or less than) the size of the T-gap_T that can be defined / configured / indicated for device category 1. Alternatively, the size of the T-gap_T applied to device category 2 can be predefined or configured / indicated by the reader to be greater than (or less than) the size of the T-gap_T applied to device category 1.

[0230] Furthermore, symbols used for A-IoT communication can be represented as chips, and a chip can correspond to a modulation symbol modulated in on-off keying (OOK) or binary phase shift keying (BPSK).

[0231] In this case, the symbol index for A-IoT communication can be determined using the following Alt-1 to Alt-3. Considering the parameter set of the NR system and the target data rate of the A-IoT system, the symbol duration for A-IoT communication can be determined using one or more of the following methods. For reference, the NR system in this disclosure can be replaced by a (5G and / or 6G) wireless communication system (or a parent system or a coexisting communication system), and the (CP-)OFDM symbol can be replaced by the basic transmission time unit of the (5G and / or 6G) wireless communication system (or a parent system or a coexisting communication system).

[0232] -Alt-1: The duration of N CP-OFDM symbols in an NR system can be defined as the duration of a symbol used for A-IoT communication, and the corresponding N value can be predefined or configured / indicated to the A-IoT device.

[0233] -Alt-2: The duration of a CP-OFDM symbol in an NR system is divided into M equal parts, and one of these parts can be defined as the symbol duration used for A-IoT communication. The corresponding value of M can be predefined or configured / indicated to the A-IoT device. In this case, a CP-OFDM symbol duration may include a CP period, may not include a CP period, or may include only a portion of a CP period.

[0234] -Alt-3: One or more OFDM samples (e.g., T_c or T_s in 3GPP TS38.211) are defined as a sample group, and K sample groups can be defined as a symbol duration for A-IoT communication. The corresponding K value and the method used to determine the sample group can be predefined or configured / instructed to the A-IoT device.

[0235] One of Alt-1 to Alt-3 can be configured / applied differently or together depending on the following factors.

[0236] - Use cases for A-IoT devices (e.g., inventory, sensors, positioning, commands, etc.); - Device type of A-IoT device; - The topology of A-IoT communication; and - A-IoT Device Index.

[0237] A-IoT device indexes, which determine the size of F-gap_T and / or T-gap_T or determine the symbol indexes used for A-IoT communication, may vary depending on the situation / scenario / process, and the following types of indexes may be available.

[0238] a) Unique A-IoT Device ID: This can refer to a unique index assigned to each A-IoT device during production, similar to the Electronic Product Code (EPC) in RFID.

[0239] b) Random Number: This can be a temporary random value (e.g., an N-bit random value) generated by the A-IoT device. It can be used to identify A-IoT devices or for inventory purposes. For example, it can be a temporary random index generated by each A-IoT device in a series of processes to reduce collisions and thus allow devices to connect at random times during random access or initial access. From the reader's perspective, the specific index used as a random value by a particular device may remain unknown.

[0240] c) An index capable of identifying A-IoT devices: This can be an index used after random access or initial access has been completed, and thus enables contention resolution for identifying A-IoT devices or for inventory purposes. Specifically, it can be an index value generated by each A-IoT device and reported to the reader, or assigned to each A-IoT device by the reader. This can be similar to C-RNTI in an NR system or HANDLE in RFID, and has a shorter bit length (i.e., bit width) than the unique A-IoT device ID.

[0241] When determining F-gap_T and / or T-gap_T based on A-IoT device indices, it is beneficial from the reader's perspective if there are a large number of A-IoT devices ready to send a BSS at a specific point in time. Conversely, configuring / indicating a large number of F-gap_T and / or T-gap_T candidates may be inefficient in terms of resource utilization when the reader expects only one or a very small number of devices to send a BSS. For example, when the reader will use X kHz, 2 X kHz and 3 When X kHz is configured as an F-gap_T candidate, but the BSS is expected to be sent at the corresponding time point for a single A-IoT device application with 3 The F-gap_T corresponding to X kHz is wasted on X kHz and 2 The frequency resources corresponding to X kHz. Therefore, methods for adjusting the number of F-gap_T and / or T-gap_T candidates to apply to BSS transmission at a specific time should be considered.

[0242] In one approach for adjusting the number of candidates, the reader can configure / indicate whether an A-IoT device index is involved by parameters F-gap_T and / or T-gap_T for the A-IoT device.

[0243] For example, when a device transmits a BSS at a specific time #A or during a specific time period starting from time #A, the reader can exclude the A-IoT device index by configuring / instructing the A-IoT device with parameters for F-gap_T and / or T-gap_T. Upon receiving this signaling, the A-IoT device can generate F-gap_T and / or T-gap_T by applying rules independent of the device index and performing UL transmission to generate F-gap_T and / or T-gap_T for BSS transmission at the corresponding time. In another example, when transmitting a BSS during a specific time period, the reader can configure / instruct the device to include the A-IoT device index by parameters for F-gap_T and / or T-gap_T. Upon receiving this signaling, the A-IoT device can generate F-gap_T and / or T-gap_T by applying rules taking the device index into account and performing UL transmission to generate F-gap_T and / or T-gap_T for BSS transmission at the corresponding time.

[0244] In another approach to adjusting the number of candidates, specific rules can be used to determine whether an A-IoT device index is involved. Specifically, if an A-IoT device performs random access or initial access for identification or inventory purposes, if it sends a BSS before contention resolution, or if the A-IoT device sends a random value or index value that it generates and enables device identification, rules can be established to include the A-IoT device index as the F-gap_T and / or T-gap_T parameters.

[0245] For example, an A-IoT device performing random or initial access can generate F-gap_T and / or T-gap_T by applying rules that take into account the A-IoT device index in the BSS transmission and perform UL transmission, even without separate configuration / instruction. Conversely, for UL transmissions occurring after contention resolution or based on an index of a unique A-IoT device ID or an identifier enabling the A-IoT device, the A-IoT device can generate F-gap_T and / or T-gap_T by applying rules independent of the A-IoT device index in the BSS transmission and perform UL transmission.

[0246] In generating F-gap_T and / or T-gap_T by applying rules that consider the index of A-IoT devices, the number of F-gap_T and / or T-gap_T candidates can be configured / indicated by the reader. This is because, from the perspective of radio resource utilization, allocating a relatively large number of candidates may be efficient if a large number of A-IoT devices are expected for BSS reception, and conversely, if a smaller number of A-IoT devices are expected, a relatively small number of candidates should be allocated.

[0247] For example, when an A-IoT device transmits a BSS at a specific time #A or during a specific time period starting from time #A, the reader can configure / indicate the number of F-gap_T and / or T-gap_T candidates to be K. Upon receiving this signaling, the A-IoT device can determine an F-gap_T and / or T-gap_T to perform a UL transmission based on the mapping between the A-IoT device index and the F-gap_Ts and / or T-gap_Ts. An example of the mapping could be assigning indices from 0 to (K-1) to K candidates and selecting the F-gap_T and / or T-gap_T corresponding to the index generated by a modulo K operation on the A-IoT device index.

[0248] Alternatively, the number of F-gap_T and / or T-gap_T candidates can be determined by specific rules. Specifically, the number of candidates can be a specific K value (where K can be predefined or can be configured / indicated by the reader) if the device is performing random access or initial access for identification / inventory purposes, if the device sends a BSS before contention resolution, or if the device sends a random value or index value that enables A-IoT device identification.

[0249] For example, an A-IoT device performing random or initial access can determine an F-gap_T and / or T-gap_T based on the mapping between the A-IoT device index and K candidates, even without a separate indication. Specifically, an index from 0 to (K-1) can be assigned to K F-gap_T and / or T-gap_T candidates, and the F-gap_T and / or T-gap_T corresponding to the result of modulo K on the A-IoT device index can be selected. Conversely, after a contention is resolved or in the case of a UL transmission based on a unique A-IoT device ID or an index that enables the A-IoT device identifier, the number of F-gap_T and / or T-gap_T candidates can be only one, and the A-IoT device can generate an F-gap_T and / or T-gap_T for sending a BSS and performing a UL transmission.

[0250] In determining an F-gap_T and / or T-gap_T by applying rules independent of the A-IoT device index or based on the mapping between the A-IoT device index and F-gap_Ts and / or T-gap_Ts, the pool of F-gap_Ts available for A-IoT devices can vary depending on whether an external CW is required during BSC execution and / or whether the reader transmits a CW during the BSS transmission time. For example, because a device that generates signals internally can transmit the BSS without a CW (autonomously generating and transmitting signals internally without external CW), it may be allowed for the device to select 0 as F-gap_T. In other words, F-gap_T=0 can be included in the pool of F-gap_Ts available for A-IoT devices. In another example, if the A-IoT device can identify that the reader does not transmit a CW during a specific UL transmission time, it may be allowed for the A-IoT device to select 0 as F-gap_T during the transmission time. (In other words, F-gap_T=0 can be included in the pool of F-gap_Ts available for A-IoT devices.)

[0251] In determining an F-gap_T and / or T-gap_T by applying rules independent of the A-IoT device index or based on the mapping between the A-IoT device index and F-gap_Ts and / or T-gap_Ts, the pool of F-gap_Ts and / or T-gap_Ts available for A-IoT devices can be defined or configured / indicated differently depending on the device type and / or device category. For example, a total of two F-gap_T candidates can be configured for device type 1 / 2a, while four F-gap_T candidates can be configured for device type 2b. Each A-IoT device can perform D2R transfers by applying an F-gap_T based on its device index within the F-gap_T pool corresponding to its type.

[0252] When configuring / indicating the pool of F-gap_T candidates, the total bandwidth applicable to F-gap_T (e.g., 2) is used by A-IoT devices through {F-gap_T units}. It is also possible to derive K from combinations of Y (or Y Hz) and the number of candidates K, as well as methods for setting the F-gap_T unit (e.g., X Hz). For example, K can be determined by floor(Y / X), or if CW pitch positions are excluded, K can be determined by floor(Y / X)-1.

[0253] <Proposal 2: Methods for signal transmission in signal receivers and readers for A-IoT devices>

[0254] As described in Proposal 1, a BSS can be transmitted by applying different F-gap_T and / or T-gap_T to each A-IoT device. When a reader receives signals from one or more A-IoT devices with different F-gap_Ts at a specific time or during a specific time period, the reader may need a way to distinguish and send responses to those one or more A-IoT devices. Furthermore, A-IoT devices that have already applied F-gap_T and / or T-gap_T may need to determine whether a corresponding transmission from the reader is intended for use in its transmission.

[0255] Therefore, this disclosure proposes a method for a reader to transmit a signal corresponding to the BSS of an A-IoT device that has applied F-gap_T and / or T-gap_T. For convenience, the transmission signal from the reader corresponding to the BSS of the A-IoT device is referred to as an ACK signal.

[0256] In methods for determining whether a transmission from a reader corresponds to a signal transmitted by the A-IoT device itself, F-gap_R and / or T-gap_R can be applied to the ACK signal. Applying F-gap_R means that the reader transmits a signal by applying a frequency axis equivalent to a shift of F-gap_R at the Ref-DL frequency, which is a specific frequency (e.g., the center frequency) of the signal transmitted without F-gap_R. The Ref-DL frequency can be the same as or different from the frequency at which the CW is transmitted. Alternatively, applying T-gap_R can mean that when the A-IoT device anticipates a signal from the reader after a specific time period following its UL signal transmission, the reader transmits a signal or the A-IoT device receives a signal starting from the specific time period after T-gap_R.

[0257] Preferably, a one-to-one, one-to-one, or N-to-one mapping relationship can exist between F-gap_Ts and / or T-gap_Ts and F-gap_Rs and / or T-gap_Rs. In the example of a one-to-one mapping, candidates with the same index can be linked together by indexing K F-gap_T and / or T-gap_T candidates from 0 to (K-1) and K F-gap_R and / or T-gap_R candidates from 0 to (K-1). In this case, the K F-gap_T and / or T-gap_T candidates and the K F-gap_R and / or T-gap_R candidates can be predefined or can be configured / indicated by the reader.

[0258] Specifically, an A-IoT device that has attempted UL BSS transmission by selecting F-gap_T and / or T-gap_T corresponding to the m-th candidate can expect that F-gap_R and / or T-gap_R corresponding to the m-th candidate will be applied to the ACK signal from the reader corresponding to the UL BSS transmission. In other words, upon receiving a BSS via F-gap_T and / or T-gap_T corresponding to the m-th candidate, the reader can apply F-gap_R and / or T-gap_R corresponding to the m-th candidate when sending the ACK signal corresponding to the BSS.

[0259] More simply, rules can be defined such that the F-gap_T and / or T-gap_T applied by the A-IoT device are identical to the F-gap_R and / or T-gap_R. In this case, an A-IoT device that has already transmitted a UL signal by applying a specific F-gap_T and / or T-gap_T can determine that its UL transmission was successful by receiving an ACK signal corresponding to the UL transmission from the reader.

[0260] In another method for determining whether a transmission from the reader corresponds to a signal sent by the A-IoT device itself, the ACK signal may include information about the F-gap_T and / or T-gap_T of the signal from the A-IoT device, or a portion thereof. Including specific content in the ACK signal may mean that it consists of one or a combination of all / some of the following i) to iv). For example, when the information about the F-gap_T and / or T-gap_T includes X bits, X bits may be carried in the payload, or (X-1) bits may be carried in the payload while the remaining 1 bit is delivered by selecting one of two sequences.

[0261] i) Included in part or all of the payload carried by the ACK signal.

[0262] ii) Select one of the N sequences that can be carried by the ACK signal.

[0263] iii) Parameters related to the scrambling sequence are applied to the payload carried by the ACK signal.

[0264] iv) CRC information of the ACK signal.

[0265] When the information about F-gap_T and / or T-gap_T may include X bits, the method for configuring the X bits corresponding to F-gap_T and / or T-gap_T can be determined based on the number of predefined / configured F-gap_T and / or T-gap_T candidates.

[0266] For example, when there are K1 F-gap_T candidates and K2 T-gap_T candidates, X can be configured as X = ceiling{log2(K1)} + ceiling{log2(K2)}. In this case, the first ceiling{log2(K1)} bits can be used to signal which of the K1 F-gap_T candidates to use, and the last ceiling{log2(K2)} bits can be used to signal which of the K2 T-gap_T candidates to use. Specifically, for K1=4 and K2=1, when the A-IoT device sends a UL signal using the third F-gap_T candidate, and the 2-bit information about F-gap_T and / or T-gap_T is "10", the A-IoT device can determine that the reader has successfully received the signal it sent. Furthermore, a reader that has received the BSS via the third F-gap_T candidate can send 2-bit information about F-gap_T and / or T-gap_T, which is set to "10".

[0267] The two determination methods described above can be combined. That is, only a portion of the information about F-gap_T and / or T-gap_T can be applied to F-gap_R and / or T-gap_R of the ACK signal, while the remaining portion of the information about F-gap_T and / or T-gap_T is included in the ACK signal.

[0268] In this embodiment, although an N-to-1 mapping relationship is defined / configured between F-gap_Ts and / or T-gap_Ts and F-gap_Rs and / or T-gap_Rs, the ACK signal can carry information indicating which of the N F-gap_Ts and / or T-gap_Ts corresponds. In a specific example, when four candidates are configured for F-gap_Ts and two candidates are configured for T-gap_Ts, the F-gap_R in the ACK signal can represent one of the four F-gap_T candidates, while information about one of the two T-gap_T candidates is carried in the ACK signal.

[0269] After successfully receiving a BSS with specific F-gap_T and / or T-gap_T applied, the reader can notify of successful reception by sending an ACK signal using the aforementioned determination method (within a pre-determined or agreed-upon time or period with the A-IoT device). Alternatively, even if the reader fails to receive the BSS, it can explicitly notify of failure by sending an ACK signal using the aforementioned determination method (within a pre-determined or agreed-upon time or period with the A-IoT device). Alternatively, the reader may not perform explicit ACK transmission when the BSS is not received.

[0270] After sending a UL signal with specific F-gap_T and / or T-gap_T, the A-IoT device can identify a successful UL transmission by receiving an ACK signal using the aforementioned determination method (within a pre-determined or agreed-upon time or period with the A-IoT device). Conversely, if an ACK signal using the aforementioned determination method is received (within a pre-determined or agreed-upon time or period with the A-IoT device) but includes a reception failure message from the reader, the A-IoT device can identify a failed UL signal transmission. Alternatively, if the A-IoT device fails to receive an ACK signal using the aforementioned determination method (within a pre-determined or agreed-upon time or period with the A-IoT device), the A-IoT device can identify a failed UL signal transmission. An A-IoT device whose UL transmission has failed can attempt a retransmission after a specific time.

[0271] In another embodiment, upon successfully receiving a BSS with specific F-gap_T and / or T-gap_T applied, the reader can signal successful BSS reception by sending an ACK signal based on F-gap_T and / or T-gap_T (instead of an ACK signal based on the received F-gap_T and / or T-gap_T) to indicate that the A-IoT device will be willing to use it again in the next use (within a pre-determined or agreed-upon time or period with the A-IoT device). The A-IoT device can identify successful UL signal transmission by receiving an ACK signal after sending a UL signal with specific F-gap_T and / or T-gap_T applied (within a pre-determined or agreed-upon time or period with the A-IoT device), and can send the next UL signal by applying F-gap_T and / or T-gap_T included in the ACK signal.

[0272] In another embodiment, when the reader successfully receives a BSS with a specific F-gap_T and / or T-gap_T applied, the reader can notify of successful BSS reception by sending an ACK signal based on F-gap_T and / or T-gap_T indicating that the A-IoT device is desirable for the next use (instead of an ACK signal based on the received F-gap_T and / or T-gap_T).

[0273] For example, the A-IoT device monitors ACK signal transmission periods corresponding to the total number (e.g., K) of F-gap_T and / or T-gap_T candidates. If no ACK signal matches its own F-gap_T and / or T-gap_T during the K active signal transmission periods, the A-IoT device considers BSS reception to have failed. Conversely, if an ACK signal matches its own F-gap_T and / or T-gap_T during the K ACK signal transmission periods, the A-IoT device considers BSS reception to have been successful.

[0274] In another example, the reader can indicate how many ACK signals remain (or how many ACK signal transmission periods the A-IoT device should attempt to receive ACK signals) through each ACK signal (in addition to information about F-gap_T and / or T-gap_T). The A-IoT device can consider BSS reception to have failed when no match is found for its own F-gap_T and / or T-gap_T until the last ACK signal (i.e., until the last ACK signal transmission period). The A-IoT device can consider BSS reception to have succeeded when an ACK signal that matches its own F-gap_T and / or T-gap_T is found.

[0275] In another example, the reader can indicate whether each ACK signal is the last one, in addition to information about the F-gap_T and / or T-gap_T. The A-IoT device can consider BSS reception to have failed when no matching F-gap_T and / or T-gap_T is found until the last ACK signal. The A-IoT device can consider BSS reception to have been successful when an ACK signal matching its own F-gap_T and / or T-gap_T is found.

[0276] <Proposal 3: Implementation method for applying F-gap>

[0277] In this disclosure, the F-gap_T value can correspond to the number of periods of a square wave corresponding to the information of one bit / chip.

[0278] One chip corresponds to one modulation symbol modulated in OOK or BPSK. For example, in Manchester coding, information bit 0 can be encoded as 10, and information bit 1 can be encoded as 01. In this case, 10 or 01 means that the information bit comprises two chips.

[0279] For example, similar to Miller coding in RFID systems, a sequence obtained by multiplying a baseband waveform consisting of 0s or 1s by a square wave consisting of M cycles can be used to transmit PRDCH or D2R signals / channels. The F-gap_T candidates in this disclosure can be implemented to refer to these K values ​​of M when K values ​​of M are configured / indicated / defined (e.g., {M_1, M_2, ..., M_K} are configured / indicated / defined).

[0280] Specifically, the configuration of the K F-gap_T candidates in this disclosure, and the application of one of them to D2R communication, can mean that the A-IoT device transmits a D2R signal / channel using one of the K configured values ​​of M (e.g., M_k) by applying line coding (e.g., Miller coding). Alternatively, it can mean defining / configuring data rates for the K D2R signals / channels, and the A-IoT device transmitting the D2R signal / channel by applying one of those data rates.

[0281] Similarly, this can be applied to R2D communication scenarios. That is, a sequence obtained, such as in Miller coding, by multiplying a baseband waveform consisting of 0s or 1s by a square wave consisting of M cycles, can be used for PRDCH or R2D signal / channel transmission. In this case, K values ​​of M are configured / indicated / defined (e.g., {M_1, M_2, ..., M_K} are configured / indicated / defined), and the F-gap_R candidate in this disclosure can refer to these K values ​​of M.

[0282] Specifically, the configuration of the K F-gap_R candidates in this disclosure and the application of one of them to R2D communication can mean that the reader transmits R2D signals / channels by applying line coding (e.g., Miller coding techniques) using one of the K configuration values ​​of M (e.g., M_k) (or an M value linked to F-gap_T and / or T-gap_T).

[0283] Figure 20 This is a diagram illustrating the signal flow for transmission and reception between a reader and an A-IoT device according to this disclosure.

[0284] refer to Figure 20 In step A05, the reader can provide the A-IoT device with information about the set or pool of F-gap_T candidates and / or T-gap_T candidates.

[0285] Upon receiving this, the A-IoT device can select one of the F-gap_T candidates and / or T-gap_T candidates based on its device index in step A10, and send the BSS to the reader in step A15 by applying the selected F-gap_T and / or T-gap_T.

[0286] Upon receiving the BSS, the reader may send an ACK signal to the A-IoT device in step A20 by applying F-gap_R and / or T-gap_R corresponding to F-gap_T and / or T-gap_T to the ACK signal or by including information about F-gap_T and / or T-gap_T in the ACK signal.

[0287] Upon receiving an ACK signal, the A-IoT device can recognize that its BSS transmission was successful.

[0288] Figure 21 This is a flowchart illustrating the operations performed by an A-IoT device according to the present disclosure.

[0289] refer to Figure 21 In step B05, the A-IoT device can receive the configuration related to the first shift gap. In the case of topology #1, the configuration related to the first shift gap can be received from the BS acting as the reader, and in the case of topology #2, the configuration can be received from the intermediate node acting as the reader or directly from the BS.

[0290] Subsequently, in step B10, the A-IoT device sends a PDRCH to the reader based on the first shift gap.

[0291] Specifically, when the first shift gap is a frequency shift gap, the center frequency of the PDRCH is shifted from the reference frequency by at least one first shift gap. Conversely, when the first shift gap is a time shift gap, the transmission time of the PDRCH is shifted from the reference time by at least one first shift gap.

[0292] Specifically, when two or more first shift gaps are received from the reader, the A-IoT device selects one of the two or more first shift gaps based on its device index and applies the selected first shift gap to the PDRCH.

[0293] Finally, in step B15, the A-IoT device receives the PRDCH associated with the PDRCH from the reader.

[0294] Preferably, the PRDCH can be received based on a second shift gap corresponding to the first shift gap. Alternatively, the PRDCH may include information related to the first shift gap.

[0295] Figure 22 This is a flowchart illustrating the operations performed by the reader according to this disclosure.

[0296] refer to Figure 22 In step C05, the reader sends the configuration related to the first shift gap to the A-IoT device. However, depending on the topology configuration, the configuration related to the first shift gap can be sent directly to the A-IoT device from a node other than the reader (e.g., from the BS controlling the reader if the reader is a UE).

[0297] Subsequently, in step C10, the reader receives the PDRCH from the A-IoT device based on the first shift gap.

[0298] Specifically, when the first shift gap is a frequency shift gap, the center frequency of the PDRCH is shifted from the reference frequency by at least one first shift gap. When the first shift gap is a time shift gap, the transmission time of the PDRCH is shifted from the reference time by at least one first shift gap.

[0299] Finally, in step C15, the reader sends the PRDCH associated with the PDRCH to the A-IoT device.

[0300] Preferably, the PRDCH can be transmitted based on a second shift gap corresponding to the first shift gap. Alternatively, the PRDCH may include information related to the first shift gap.

[0301] In situations where multiple A-IoT devices may coexist for a single reader, each A-IoT device can perform UL transmission by applying different F-gap and / or T-gap, thereby reducing the probability of collisions and thus increasing communication efficiency.

[0302] The above embodiments are combinations of components and features of this disclosure in specific forms. Each component or feature should be considered selectively unless otherwise stated. Each component or feature may be implemented without combination with other components or features. It is also possible to combine some components and / or features to form embodiments of this disclosure. The order of operations described in the embodiments of this disclosure may be changed. Some configurations or features of one embodiment may be included in another embodiment, or may be replaced with corresponding configurations or features of another embodiment. Obviously, claims that do not have an explicit reference relationship in the claims may be combined to form embodiments or included as new claims after submission by modification.

[0303] It will be apparent to those skilled in the art that this disclosure may be embodied in other specific forms without departing from its characteristics. Therefore, the foregoing detailed description should not be construed as limiting in all respects, but rather as illustrative. The scope of this disclosure should be determined by a reasonable interpretation of the appended claims, and all variations within the equivalent scope of this disclosure are included within its scope.

[0304] Industrial applicability

[0305] This disclosure can be used in UEs, BSs or other devices in wireless communication systems.

Claims

1. A method performed by an environmental Internet of Things (IoT) device, comprising: Receive configuration associated with at least one first shift gap; Based on the at least one first shift gap, a physical device is sent to the reader via the reader channel (PDRCH); and The reader receives the physical reader-to-device channel (PRDCH) associated with the PDRCH.

2. The method according to claim 1, wherein, Based on the at least one first shift gap including a frequency shift gap, the center frequency of the PDRCH is shifted from the reference frequency by the at least one first shift gap.

3. The method according to claim 2, wherein, The frequency shift gap is related to the number of periods of the square wave used for the PDRCH.

4. The method according to claim 1, wherein, Based on the at least one first shift gap including a time shift gap, the transmission time of the PDRCH is shifted from the reference time by the at least one first shift gap.

5. The method according to claim 1, wherein, Based on the fact that the number of the first shift gaps is two or more, sending the PDRCH includes: One of two or more first shift gaps is selected based on a device index determined to be a random value; and Apply the selected first shift gap to the PDRCH.

6. The method according to claim 1, wherein, The PRDCH is received based on a second shift gap corresponding to the at least one first shift gap.

7. The method according to claim 1, wherein, The PRDCH includes information related to the at least one first shift gap.

8. The method according to claim 1, wherein, Receive the configuration associated with the at least one first shift gap from the base station (BS) or intermediate node, and The reader is at least one of the BS or the intermediate node.

9. An environmental Internet of Things (IoT) device in a wireless communication system, comprising: At least one processor; as well as At least one computer memory storing instructions that, when executed by the at least one processor, cause the environmental IoT device to perform operations. The operation includes: Receive configuration associated with at least one first shift gap; Based on the at least one first shift gap, a physical device is sent to the reader via the reader channel (PDRCH); and The reader receives the physical reader-to-device channel (PRDCH) associated with the PDRCH.

10. The environmental IoT device according to claim 9, wherein, Based on the at least one first shift gap including a frequency shift gap, the center frequency of the PDRCH is shifted from the reference frequency by the at least one first shift gap.

11. The environmental IoT device according to claim 10, wherein, The frequency shift gap is related to the number of periods of the square wave used for the PDRCH.

12. The environmental IoT device according to claim 9, wherein, Based on the at least one first shift gap including a time shift gap, the transmission time of the PDRCH is shifted from the reference time by the at least one first shift gap.

13. The environmental IoT device according to claim 9, wherein, Based on the fact that the number of the first shift gaps is two or more, sending the PDRCH includes: One of two or more first shift gaps is selected based on a device index determined to be a random value; and Apply the selected first shift gap to the PDRCH.

14. The environmental IoT device according to claim 9, wherein, The PRDCH is received based on a second shift gap corresponding to the at least one first shift gap.

15. The environmental IoT device according to claim 9, wherein, The PRDCH includes information related to the at least one first shift gap.

16. The environmental IoT device according to claim 9, wherein, Receive the configuration associated with the at least one first shift gap from the base station (BS) or intermediate node, and The reader is at least one of the BS or the intermediate node.

17. A processing apparatus in a wireless communication system, comprising: At least one processor; as well as At least one computer memory storing instructions that, when executed by the at least one processor, cause an environmental Internet of Things (IoT) device to perform operations. The operation includes: Receive configuration associated with at least one first shift gap; Based on the at least one first shift gap, a physical device is sent to the reader via the reader channel (PDRCH); and The reader receives the physical reader-to-device channel (PRDCH) associated with the PDRCH.

18. A non-transitory computer-readable storage medium storing at least one program code, said at least one program code, when executed by at least one processor, causing an environmental Internet of Things (IoT) device to perform operations. in, The operation includes: Receive configuration associated with at least one first shift gap; Based on the at least one first shift gap, a physical device is sent to the reader via the reader channel (PDRCH); and The reader receives the physical reader-to-device channel (PRDCH) associated with the PDRCH.

19. A method executed by a reader, comprising: Based on at least one first shift gap, a physical device to reader channel (PDRCH) is received from an environmental Internet of Things (IoT) device. as well as Send the physical reader associated with the PDRCH to the device channel (PRDCH) to the environmental IoT device.

20. The method of claim 19, further comprising: Send the configuration related to the at least one first shift gap to the environmental IoT device.

21. The method of claim 19, wherein, The PRDCH is transmitted based on a second shift gap corresponding to the at least one first shift gap.

22. The method according to claim 19, wherein, The PRDCH includes information related to the at least one first shift gap.

23. A reader in a wireless communication system, comprising: At least one processor; as well as At least one computer memory stores instructions that, when executed by the at least one processor, cause the reader to perform an operation. The operation includes: Based on at least one first shift gap, a physical device-to-reader channel (PDRCH) is received from an environmental Internet of Things (IoT) device; and Send the physical reader associated with the PDRCH to the device channel (PRDCH) to the environmental IoT device.

24. The reader of claim 23, wherein the operation further comprises: Send the configuration related to the at least one first shift gap to the environmental IoT device.

25. The reader according to claim 23, wherein, The PRDCH is transmitted based on a second shift gap corresponding to the at least one first shift gap.

26. The reader according to claim 23, wherein, The PRDCH includes information related to the at least one first shift gap.

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