Device and method for forming entanglement between transmitting node and receiving node on basis of dynamic lattice transformation in communication system

Abstract

The present disclosure is for performing quantum communication using a quantum entangled state in a communication system, and in which an operation method of a first device may comprise the steps of: acquiring system information; performing an initial access procedure on the basis of the system information; receiving information related to a network configuration from a control device; receiving information related to measuring from the control device; performing a measuring procedure on the basis of the information related to measuring; reporting a measurement result to the control device; and receiving, from the control device, information related to a path determined on the basis of the measurement result.

Description

Device and method for forming entanglement between a transmitting node and a receiving node based on dynamic grid transformation in a communication system

[0001] The present disclosure relates to a wireless communication system, and to a device and method for forming entanglement between a transmitting node and a receiving node based on dynamic lattice transformation in a wireless communication system.

[0002] Wireless access systems are widely deployed to provide various types of communication services, such as voice and data. Typically, wireless access systems are multiple access systems that support communications with multiple users by sharing available system resources (e.g., bandwidth, transmission power). Examples of multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single-carrier frequency division multiple access (SC-FDMA).

[0003] In particular, as numerous communication devices demand greater communication capacity, enhanced mobile broadband (eMBB) communication technologies are being proposed, improving upon existing radio access technology (RAT). Furthermore, massive machine type communications (mMTC), which connects multiple devices and objects to provide diverse services anytime and anywhere, as well as communication systems that consider reliability and latency-sensitive services / user equipment (UE), are being proposed. Various technological configurations are being proposed for these solutions.

[0004] The present disclosure relates to a device and method for forming entanglement between a transmitting node and a receiving node based on dynamic lattice transformation in a communication system.

[0005] The present disclosure relates to a device and method for forming a multi-hop segment in a communication system.

[0006] The present disclosure relates to a device and method for forming a network grid structure using multi-hop segments in a communication system.

[0007] The present disclosure relates to a device and method for determining a network configuration mode in a communication system.

[0008] The present disclosure relates to a device and method for dynamically setting the operation mode of nodes set within a network configuration mode for each sub-network in a communication system.

[0009] The present disclosure relates to a device and method for forming a maximally entangled state between vertex nodes included in a 2-hop segment using an intermediate node in a communication system.

[0010] The present disclosure relates to a device and method for determining a path between a transmitting node and a receiving node using a 2-hop segment in which a maximum entanglement state is formed in a communication system.

[0011] The present disclosure relates to a device and method for establishing sub-networks that can operate in parallel in a communication system.

[0012] The present disclosure relates to a device and method for simultaneously supporting multiple transmission and reception flows in a communication system.

[0013] The present disclosure relates to a device and method for providing a network structure suitable for QoS (quality of service) characteristics in a communication system.

[0014] The present disclosure relates to a device and method for performing communication based on entanglement percolation in a communication system.

[0015] The present disclosure relates to a device and method for configuring an entire network having a triangular lattice structure in a communication system into sub-networks having a square lattice structure or a kagome lattice structure.

[0016] The present disclosure relates to a device and method for converting a sub-network having a Kagome lattice structure into a square lattice structure based on dynamic lattice transformation in a communication system.

[0017] The technical objectives to be achieved in the present disclosure are not limited to those mentioned above, and other technical tasks not mentioned can be considered by a person having ordinary skill in the technical field to which the technical configuration of the present disclosure is applied from the embodiments of the present disclosure described below.

[0018] As an example of the present disclosure, a method performed by a first device in a communication system includes the steps of: acquiring system information; performing an initial connection procedure based on the system information; receiving information regarding a network configuration from a control device; receiving information regarding a measurement from the control device; performing a measurement procedure based on the information regarding the measurement; reporting a measurement result to the control device; and receiving information regarding a path determined based on the measurement result from the control device, wherein the information regarding the network configuration includes information indicating a network configuration mode in which a first sub-network is set; and the information regarding the measurement includes information regarding an operation mode of the first device that is dynamically set for the first sub-network, wherein the path may include at least one maximally entangled multi-hop segment.

[0019] As an example of the present disclosure, a method performed by a control device in a communication system includes the steps of transmitting system information, performing an initial connection procedure, transmitting information about a network configuration to a first device, transmitting information about a measurement to the first device, receiving a measurement result from the first device, and transmitting information about a path determined based on the measurement result to the first device, wherein the information about the network configuration includes information indicating a network configuration mode in which a first subnetwork is set, the information about the measurement includes information about an operation mode of the first device that is dynamically set for the first subnetwork, and the path may include at least one maximally entangled multi-hop segment.

[0020] As an example of the present disclosure, in a communication system, a first device includes a transceiver and a processor coupled to the transceiver, wherein the processor is configured to obtain system information, perform an initial connection procedure based on the system information, receive information regarding a network configuration from a control device, receive information regarding a measurement from the control device, perform a measurement procedure based on the information regarding the measurement, report a measurement result to the control device, and receive information regarding a path determined based on the measurement result from the control device, wherein the information regarding the network configuration includes information indicating a network configuration mode in which a first sub-network is set, and the information regarding the measurement includes information regarding an operation mode of the first device that is dynamically set for the first sub-network, and wherein the path may include at least one maximally entangled multi-hop segment.

[0021] As an example of the present disclosure, in a communication system, a control device includes a transceiver and a processor coupled to the transceiver, wherein the processor is configured to transmit system information, perform an initial connection procedure, transmit information regarding a network configuration to a first device, transmit information regarding a measurement to the first device, receive a measurement result from the first device, and transmit information regarding a path determined based on the measurement result to the first device, wherein the information regarding the network configuration includes information indicating a network configuration mode in which a first sub-network is set, and the information regarding the measurement includes information regarding an operation mode of the first device that is dynamically set for the first sub-network, and wherein the path may include at least one maximally entangled multi-hop segment.

[0022] As an example of the present disclosure, a communication device includes at least one processor, and at least one computer memory connected to the at least one processor and storing instructions that, when executed by the at least one processor, direct operations, the operations including: obtaining system information; performing an initial connection procedure based on the system information; receiving information about a network configuration from a control device; receiving information about a measurement from the control device; performing a measurement procedure based on the information about the measurement; reporting a measurement result to the control device; and receiving information about a path determined based on the measurement result from the control device, wherein the information about the network configuration includes information indicating a network configuration mode in which a first sub-network is set; and the information about the measurement includes information about an operation mode of the first device that is dynamically set for the first sub-network, and wherein the path may include at least one maximally entangled multi-hop segment.

[0023] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction includes at least one instruction executable by a processor, wherein the at least one instruction configures a device to acquire system information, perform an initial connection procedure based on the system information, receive information about a network configuration from a control device, receive information about a measurement from the control device, perform a measurement procedure based on the information about the measurement, report a measurement result to the control device, and receive information about a path determined based on the measurement result from the control device, wherein the information about the network configuration includes information indicating a network configuration mode in which a first sub-network is set, and the information about the measurement includes information about an operation mode of the first device that is dynamically set for the first sub-network, and wherein the path may include at least one maximally entangled multi-hop segment.

[0024] The above-described aspects of the present disclosure are only some of the preferred embodiments of the present disclosure, and various embodiments reflecting the technical features of the present disclosure can be derived and understood by a person having ordinary skill in the art based on the detailed description of the present disclosure to be described below.

[0025] The following effects may be achieved by embodiments based on the present disclosure.

[0026] According to the present disclosure, communication can be performed efficiently using entanglement percolation.

[0027] The effects that can be obtained from the embodiments of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly derived and understood by those skilled in the art to which the technical configuration of the present disclosure is applied, from the description of the embodiments of the present disclosure below. In other words, unintended effects resulting from implementing the configuration described in the present disclosure can also be derived from the embodiments of the present disclosure by those skilled in the art.

[0028] The accompanying drawings are intended to aid understanding of the present disclosure and, together with detailed descriptions, may provide embodiments of the present disclosure. However, the technical features of the present disclosure are not limited to specific drawings, and the features disclosed in each drawing may be combined with each other to form new embodiments. Reference numerals in each drawing may indicate structural elements.

[0029] Figure 1 illustrates an example of a communication system applicable to the present disclosure.

[0030] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0031] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure.

[0032] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure.

[0033] FIG. 5 illustrates an example of a communication structure that can be provided in a 6G (6th generation) system applicable to the present disclosure.

[0034] Figure 6 illustrates an electromagnetic spectrum applicable to the present disclosure.

[0035] Figure 7 illustrates a transmitter structure applicable to the present disclosure.

[0036] Figure 8 illustrates an example of a functional framework for application of artificial intelligence technology applicable to the present disclosure.

[0037] Figure 9 illustrates an example of a procedure for utilizing an artificial intelligence model applicable to the present disclosure.

[0038] Figure 10 illustrates a communication procedure based on AI (artificial intelligence) technology applicable to the present disclosure.

[0039] FIGS. 11A to 11D illustrate examples of a network topology in the form of a grid graph according to one embodiment of the present disclosure.

[0040] Figure 12 illustrates an example of percolation probability in a two-dimensional lattice structure applicable to the present disclosure.

[0041] FIG. 13 illustrates an example of a honeycomb grid-based sub-network configuration method according to one embodiment of the present disclosure.

[0042] FIG. 14 illustrates an example of a Kagome grid-based network configuration method according to one embodiment of the present disclosure.

[0043] FIG. 15a and FIG. 15b illustrate examples of a dynamic lattice transformation-based entanglement penetration technique according to one embodiment of the present disclosure.

[0044] FIGS. 16a and 16b illustrate another example of a dynamic lattice transformation-based entanglement penetration technique according to one embodiment of the present disclosure.

[0045] FIG. 17 illustrates an example of a 2-hop segment according to one embodiment of the present disclosure.

[0046] FIG. 18 illustrates an example of a procedure in which a first node performs entanglement percolation according to one embodiment of the present disclosure.

[0047] FIG. 19 illustrates an example of a procedure in which a control node performs entanglement penetration according to one embodiment of the present disclosure.

[0048] FIG. 20 illustrates an example of a procedure in which a first node performs route setting according to one embodiment of the present disclosure.

[0049] FIG. 21 illustrates an example of a procedure in which a control node performs route setting according to one embodiment of the present disclosure.

[0050] FIG. 22 illustrates an example of a procedure in which a first vertex node reports measurement results according to one embodiment of the present disclosure.

[0051] FIG. 23 illustrates an example of a procedure for a relay node to perform measurements according to one embodiment of the present disclosure.

[0052] FIG. 24 illustrates an example of a procedure in which a first node receives information about a network configuration mode determined by a control node according to one embodiment of the present disclosure.

[0053] FIG. 25 illustrates an example of a procedure in which a control node dynamically transmits information about a network configuration mode according to one embodiment of the present disclosure.

[0054] FIG. 26 illustrates an example flowchart of a lattice transformation-based entanglement infiltration procedure according to one embodiment of the present disclosure.

[0055] FIG. 27 illustrates an example in which qUE performs a lattice transformation-based entanglement infiltration procedure according to one embodiment of the present disclosure.

[0056] FIG. 28 illustrates an example of a procedure for a qNB to perform lattice transformation-based entanglement penetration according to one embodiment of the present disclosure.

[0057] FIG. 29 illustrates a first example of signaling for performing a lattice transformation-based entanglement infiltration procedure according to one embodiment of the present disclosure.

[0058] FIG. 30 illustrates a second example of signaling for performing a lattice transformation-based entanglement infiltration procedure according to one embodiment of the present disclosure.

[0059] FIG. 31 shows the results of comparing the entanglement penetration performance of the proposed technique and the honeycomb lattice structure according to one embodiment of the present disclosure.

[0060] Figure 32 shows the results of comparing the network resource efficiency of the proposed technique and the honeycomb lattice structure according to one embodiment of the present disclosure.

[0061] Figure 33 illustrates an example of a wireless device applicable to the present disclosure.

[0062] Figure 34 illustrates an example of a portable device applicable to the present disclosure.

[0063] FIG. 35 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0064] Figure 36 illustrates an example of a vehicle applicable to the present disclosure.

[0065] FIG. 37 illustrates an example of an extended reality (XR) device applicable to the present disclosure.

[0066] Figure 38 illustrates an example of a robot applicable to the present disclosure.

[0067] Figure 39 illustrates an example of an AI device applicable to the present disclosure.

[0068] Figure 40 illustrates an example of a quantum communication device applicable to the present disclosure.

[0069] The following embodiments combine the components and features of the present disclosure in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, some components and / or features may be combined to form embodiments of the present disclosure. The order of operations described in the embodiments of the present disclosure may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment.

[0070] In the description of the drawings, procedures or steps that may obscure the gist of the present disclosure are not described, and procedures or steps that can be understood by a person skilled in the art are also not described.

[0071] Throughout the specification, when a part is said to "comprising" or "including" a component, this does not mean that other components may be included, but rather that other components may be excluded, unless otherwise specifically stated. In addition, terms such as "...part," "...unit," and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software. In addition, the words "a" or "an," "one," "the," and similar related words may be used in the context of describing the present disclosure (especially in the context of the claims below) to include both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context.

[0072] Embodiments of the present disclosure described herein focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station is understood as a terminal node of a network that directly communicates with the mobile station. Certain operations described herein as being performed by the base station may, in some cases, be performed by an upper node of the base station.

[0073] That is, in a network consisting of multiple network nodes including a base station, various operations performed for communication with a mobile station may be performed by the base station or other network nodes other than the base station. In this case, the term 'base station' may be replaced by terms such as fixed station, Node B, eNB (eNode B), gNB (gNode B), ng-eNB, advanced base station (ABS), or access point.

[0074] Additionally, in the embodiments of the present disclosure, the term terminal may be replaced with terms such as user equipment (UE), mobile station (MS), subscriber station (SS), mobile subscriber station (MSS), mobile terminal, or advanced mobile station (AMS).

[0075] Additionally, a transmitter refers to a fixed and / or mobile node that provides data or voice services, and a receiver refers to a fixed and / or mobile node that receives data or voice services. Therefore, for uplink, a mobile station can be the transmitter, and a base station can be the receiver. Similarly, for downlink, a mobile station can be the receiver, and a base station can be the transmitter.

[0076] Embodiments of the present disclosure may be supported by standard documents disclosed in at least one of wireless access systems, such as IEEE 802.xx system, 3rd Generation Partnership Project (3GPP) system, 3GPP Long Term Evolution (LTE) system, 3GPP 5th generation (5G) NR (New Radio) system and 3GPP2 system, and in particular, embodiments of the present disclosure may be supported by 3GPP TS (technical specification) 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents.

[0077] Furthermore, the embodiments of the present disclosure can be applied to other wireless access systems and are not limited to the systems described above. For example, they can be applied to systems implemented after the 3GPP 5G NR system and are not limited to a specific system.

[0078] That is, obvious steps or parts not described in the embodiments of the present disclosure can be explained by referring to the above documents. In addition, all terms disclosed in this document can be explained by the above standard documents.

[0079] Hereinafter, preferred embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description set forth below, together with the accompanying drawings, is intended to illustrate exemplary embodiments of the present disclosure and is not intended to represent the only embodiments in which the technical configurations of the present disclosure may be implemented.

[0080] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding of the present disclosure, and the use of such specific terms may be changed to other forms without departing from the technical spirit of the present disclosure.

[0081] The following technology can be applied to various wireless access systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access).

[0082]

[0083] For clarity, the following description is based on 3GPP communication systems (e.g., LTE, NR, etc.), but the technical spirit of the present disclosure is not limited thereto. LTE may refer to technology after 3GPP TS 36.xxx Release 8. Specifically, LTE technology after 3GPP TS 36.xxx Release 10 may be referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 may be referred to as LTE-A pro. 3GPP NR may refer to technology after TS 38.xxx Release 15. 3GPP 6G may refer to technology after TS Release 17 and / or Release 18. "xxx" refers to a standard document detail number. LTE / NR / 6G may be collectively referred to as a 3GPP system.

[0084] For background information, terms, abbreviations, etc. used in this disclosure, reference may be made to standard documents published prior to this disclosure. For example, reference may be made to standard documents 36.xxx and 38.xxx.

[0085]

[0086] Communication system applicable to the present disclosure

[0087] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts of the present disclosure disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0088] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0089] Figure 1 illustrates an example of a communication system applied to the present disclosure.

[0090] Referring to FIG. 1, a communication system (100) applied to the present disclosure includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (extended reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI (artificial intelligence) device / server (100g). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicles (100b-1, 100b-2) may include unmanned aerial vehicles (UAVs) (e.g., drones). The XR devices (100c) include augmented reality (AR) / virtual reality (VR) / mixed reality (MR) devices, and may be implemented in the form of head-mounted devices (HMDs), head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, etc. The portable devices (100d) may include smartphones, smart pads, wearable devices (e.g., smartwatches, smart glasses), computers (e.g., laptops, etc.), etc. The home appliances (100e) may include TVs, refrigerators, washing machines, etc. The IoT devices (100f) may include sensors, smart meters, etc.For example, the base station (120) and the network (130) may also be implemented as wireless devices, and a specific wireless device (120a) may act as a base station / network node to other wireless devices.

[0091] Wireless devices (100a to 100f) can be connected to a network (130) via a base station (120). AI technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (100g) via a network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR), or a 6G network. The wireless devices (100a to 100f) can communicate with each other via the base station (120) / network (130), but can also communicate directly (e.g., sidelink communication) without going through the base station (120) / network (130). For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (vehicle to vehicle) / V2X (vehicle to everything) communication). Additionally, an IoT device (100f) (e.g., a sensor) can communicate directly with another IoT device (e.g., a sensor) or another wireless device (100a to 100f).

[0092] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a to 100f) / base stations (120), and base stations (120) / base stations (120). Here, the wireless communication / connection can be established through various wireless access technologies such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and base station-to-base station communication (150c) (e.g., relay, IAB (integrated access backhaul)). Through the wireless communication / connection (150a, 150b, 150c), the wireless device and base station / wireless device, and base stations and base stations can transmit / receive wireless signals to / from each other. For example, the wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on various proposals of the present disclosure, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), resource allocation processes, etc. may be performed.

[0093]

[0094] Devices applicable to the present disclosure

[0095] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0096] Referring to FIG. 2, the wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G). The wireless device (200) includes at least one processor (202) and at least one memory (204), and may additionally include at least one transceiver (206) and / or at least one antenna (208).

[0097] The processor (202) controls the memory (204) and / or the transceiver (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (206). In addition, the processor (202) may receive a wireless signal including second information / signal via the transceiver (206), and then store information obtained from signal processing of the second information / signal in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may store software code including instructions for performing some or all of the processes controlled by the processor (202), or for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology. The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via at least one antenna (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF (radio frequency) unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0098] Hereinafter, the hardware elements of the wireless device (200) will be described in more detail. Although not limited thereto, at least one protocol layer may be implemented by at least one processor (202). For example, at least one processor (202) may implement at least one layer (e.g., a functional layer 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 a message, 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) can generate a signal (e.g., a baseband signal) including a PDU, an SDU, a message, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this document, and provide the signal to at least one transceiver (206). At least one processor (202) can receive a signal (e.g., a baseband signal) from at least one transceiver (206) and obtain the PDU, SDU, message, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document.

[0099] At least one processor (202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. The at least one processor (202) may be implemented by hardware, firmware, software, or a combination thereof. For example, at least one application 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 the at least one processor (202). The descriptions, functions, procedures, 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, procedures, functions, etc. The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be included in the at least one processor (202), or may be stored in at least one memory (204) and executed by the at least one processor (202). The descriptions, functions, procedures, suggestions, methods and / or flowcharts disclosed in this document may be implemented using firmware or software in the form of code, instructions and / or sets of instructions.

[0100] At least one memory (204) can be connected to at least one processor (202) and can store various forms of data, signals, messages, information, programs, codes, instructions and / or commands. The at least one memory (204) can be configured as a read only memory (ROM), a random access memory (RAM), an erasable programmable read only memory (EPROM), a flash memory, a hard drive, a register, a cache memory, a computer readable storage medium and / or a combination thereof. The at least one memory (204) can be located internally and / or externally to the at least one processor (202). In addition, the at least one memory (204) can be connected to the at least one processor (202) via various technologies such as a wired or wireless connection.

[0101] At least one transceiver (206) can transmit user data, control information, wireless signals / channels, etc., mentioned in the methods and / or flowcharts of this document to at least one other device. At least one transceiver (206) can receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or 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) and can transmit and receive wireless signals. For example, at least one processor (202) can control at least one transceiver (206) to transmit user data, control information, or wireless signals to at least one other device. Furthermore, at least one processor (202) can control at least one transceiver (206) to receive user data, control information, or wireless signals from at least one other device. In addition, at least one transceiver (206) may be connected to at least one antenna (208), and at least one transceiver (206) may be configured to transmit and receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or operation flowcharts disclosed in this document through at least one antenna (208). In this document, at least one antenna may be a plurality of physical antennas or a plurality of logical antennas (e.g., antenna ports). At least one transceiver (206) may convert the received wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using at least one processor (202). At least one transceiver (206) may convert the processed user data, control information, wireless signals / channels, etc. from baseband signals to RF band signals using at least one processor (202).For this purpose, at least one transceiver (206) may include an (analog) oscillator and / or filter.

[0102] The components of the wireless device described with reference to FIG. 2 may be referred to by different terms in terms of functionality. For example, the processor (202) may be referred to as a control unit, the transceiver (206) as a communication unit, and the memory (204) as a storage unit. In some cases, the communication unit may be used to mean at least a portion of the processor (202) and the transceiver (206).

[0103] The structure of the wireless device described with reference to FIG. 2 can be understood as the structure of at least a portion of various devices. For example, the structure of the wireless device illustrated in FIG. 2 can be at least a portion of various devices described with reference to FIG. 1 (e.g., a robot (100a), a vehicle (100b-1, 100b-2), an XR device (100c), a portable device (100d), a home appliance (100e), an IoT device (100f), an AI device / server (100g)). Furthermore, according to various embodiments, in addition to the components illustrated in FIG. 2, the device may further include other components.

[0104] For example, the device may be a portable device such as a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), or a portable computer (e.g., a laptop, etc.). In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an interface unit that includes at least one port for connection with another device (e.g., an audio input / output port, a video input / output port), and an input / output unit for inputting and outputting image information / signals, audio information / signals, data, and / or information input from a user.

[0105] For example, the device may be a mobile device such as a mobile robot, a vehicle, a train, an aerial vehicle (AV), a ship, etc. In this case, the device may further include at least one of a driving unit including at least one of an engine, a motor, a power train, wheels, brakes, and a steering unit of the device, a power supply unit including a wired / wireless charging circuit, a battery, etc. that supplies power, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, an autonomous driving unit that performs functions such as path maintenance, speed control, and destination setting, and a position measurement unit that obtains location information of the mobile device through a global positioning system (GPS) and various sensors.

[0106] For example, the device may be an XR device such as an 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, a robot, etc. In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an input / output unit that obtains control information, data, etc. from the outside and outputs the generated XR object, and a sensor unit that senses status information, environmental information, and user information of the device or the surroundings of the device.

[0107] For example, the device may be a robot that can be classified into industrial, medical, household, military, etc. types depending on the purpose or field of use. In this case, the device may further include at least one of a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a driving unit that performs various physical actions, such as moving the robot joints.

[0108] For example, the device may be an AI device such as a TV, a projector, a smartphone, a PC, a laptop, a digital broadcasting terminal, a tablet PC, a wearable device, a set-top box (STB), a radio, a washing machine, a refrigerator, digital signage, a robot, a vehicle, etc. In this case, the device may further include at least one of an input unit that acquires various types of data from the outside, an output unit that generates output related to sight, hearing, or touch, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a training unit that trains a model composed of an artificial neural network using learning data.

[0109] The structure of the wireless device illustrated in FIG. 2 may be understood as a part of a RAN node (e.g., a base station, DU, RU, RRH, etc.). That is, the device illustrated in FIG. 2 may be a RAN node. In this case, the device may further include a wired transceiver for front haul and / or back haul communications. However, if the front haul and / or back haul communications are based on wireless communications, at least one transceiver (206) illustrated in FIG. 2 may be used for front haul and / or back haul communications, and a wired transceiver may not be included.

[0110]

[0111] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure. For example, the transmission signal may be processed by a signal processing circuit. At this time, the signal processing circuit (300) may include scramblers (310), modulators (320), a layer mapper (330), a precoder (340), resource mappers (350), and signal generators (360). At this time, for example, the operation / function of FIG. 3 may be performed in the processor (202) and / or the transceiver (206) of FIG. 2. Furthermore, for example, the hardware elements of FIG. 3 may be implemented in the processor (202) and / or the transceiver (206) of FIG. 2. For example, blocks 310 to 360 may be implemented in the processor (202) of FIG. 2. Additionally, blocks 310 to 350 may be implemented in the processor (202) of FIG. 2, and block 360 may be implemented in the transceiver (206) of FIG. 2, and are not limited to the above-described embodiment.

[0112] The codeword can be converted into a wireless signal through the signal processing circuit (300) of FIG. 3. Here, the codeword is an encoded bit sequence of an information block. The information block may include a transport block (e.g., a UL-SCH transport block, a DL-SCH transport block). Here, the information block may include data related to AI (e.g., training data, AI model data, input data, output data, etc.), and the codeword may be an encoded bit sequence corresponding to the data related to AI. The wireless signal may be transmitted through various physical channels (e.g., a PUSCH, a PDSCH). Specifically, the codeword may be converted into a bit sequence scrambled by scramblers (310). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence may be modulated into a modulation symbol sequence by modulators (320). Modulation schemes may include pi / 2-BPSK (pi / 2-binary phase shift keying), m-PSK (m-phase shift keying), m-QAM (m-quadrature amplitude modulation), etc.

[0113] A complex modulation symbol sequence can be mapped to at least one transport layer by a layer mapper (330). Here, a transport layer is a logical resource unit for mapping a signal or data transmitted through spatial resources to antenna ports, and one transport layer can correspond to one stream or one antenna port. Each of the complex modulation symbols included in the complex modulation symbol sequence is mapped to at least one transport layer, thereby determining which antenna port it will be transmitted through. The modulation symbols of each transport layer can be mapped to the corresponding antenna port(s) by a precoder (340). The output z of the precoder (340) can be obtained by multiplying the output y of the layer mapper (330) by a precoding matrix W of NХM. Here, N is the number of antenna ports, and M is the number of transport layers. Here, the precoder (340) may perform precoding after performing transform precoding (e.g., discrete Fourier transform (DFT)) on complex modulation symbols. Additionally, the precoder (340) may perform precoding without performing transform precoding.

[0114] Resource mappers (350) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources may include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. Signal generators (360) generate wireless signals from the mapped modulation symbols, and the generated wireless signals can be transmitted to other devices through each antenna. To this end, each of the signal generators (360) may include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, etc.

[0115] The signal processing process for a received signal in a wireless device may be configured in reverse order of the signal processing process (310 to 360) of FIG. 3. For example, a wireless device (e.g., 200 of FIG. 2) may receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal may be converted into a baseband signal through a signal restorer. For this purpose, the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal may be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codeword may be restored to the original information block through decoding. Therefore, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource demapper, a postcoder, a demodulator, a descrambler, and a decoder.

[0116] The signal processing circuit (300) described with reference to FIG. 3 is exemplified as including a plurality of scramblers (310), modulators (320), a plurality of resource mappers (350), and a plurality of signal generators (360). However, at least one of the scramblers, modulators, resource mappers, and signal generators may be implemented as a single integrated structure. That is, the number of at least one of the scramblers, modulators, resource mappers, and signal generators may be smaller than the number of layers. Furthermore, at least one of the components exemplified in FIG. 3 may be omitted.

[0117]

[0118] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure. Figure 4 illustrates operations of a terminal (410) and a base station (420) transmitting and / or receiving data and operations performed prior thereto.

[0119] Referring to FIG. 4, in step 401, the terminal (410) and the base station (420) perform synchronization. For example, the terminal (410) performs an initial cell search operation. Specifically, the terminal (410) can detect at least one synchronization signal transmitted from the base station (420) according to a predefined rule. Here, the synchronization signal can include multiple synchronization signals classified according to structure or purpose (e.g., primary synchronization signal, secondary synchronization signal). Through this, the terminal (410) can check the boundary of the frame, subframe, slot, and / or symbol of the base station (420) and obtain information about the base station (420) (e.g., cell identifier).

[0120] In step 403, the terminal (410) obtains system information transmitted from the base station (420). The system information is information related to the properties, characteristics, and / or capabilities of the base station (420) required to access the base station (420) and use the service, and may be classified by content (e.g., whether it is essential for access), transmission structure (e.g., channel used, whether provided on-demand), etc., and may be classified into, for example, a master information block (MIB) and a system information block (SIB). If necessary, the terminal (410) may transmit a signal requesting system information before receiving the system information. The system information may include information related to an AI function. For example, the system information may include at least one of information related to an AI model, information related to training, and information related to inference / prediction, as information required for operations performed based on AI. However, the request and provision of the system information may be performed after a random access procedure described below.

[0121] In step 405, the terminal (410) and the base station (420) perform a random access procedure. The terminal (410) may transmit and / or receive at least one message (e.g., a random access preamble, a random access response (RAR) message, etc.) for the random access procedure based on information related to the random access channel of the base station (420) obtained through system information (e.g., channel position, channel structure, supported preamble structure, etc.). For example, the terminal (410) may transmit a preamble (e.g., MSG1) through the random access channel, receive an RAR message (e.g., MSG2), transmit a message (e.g., MSG3) including information related to the terminal (410) (e.g., identification information) to the base station (420) using scheduling information included in the RAR message, and receive a message (e.g., MSG4) for contention resolution and / or connection establishment. As another example, MSG1 and MSG3 may be sent and received as one message, or MSG2 and MSG4 may be sent and received as one message.

[0122] In step 407, the terminal (410) and the base station (420) perform signaling of control information. Here, the control information may be defined in various layers, such as a layer that controls a connection (e.g., a radio resource control (RRC) layer), a layer that handles mapping between logical channels and transport channels (e.g., a media access control (MAC) layer), and a layer that handles physical channels (e.g., a physical (PHY) layer). For example, the terminal (410) and the base station (420) may perform at least one of signaling for establishing a connection, signaling for determining settings related to communication, and signaling for indicating allocated resources. In addition, the signaling of the control information may be performed to convey information related to an AI function. For example, the information related to an AI function is information necessary for an operation performed based on AI, and may include at least one of information related to an AI model, information related to training, and information related to inference / prediction. More specifically, information related to the AI ​​function signaled in step 407 may be combined and / or linked with information related to the AI ​​function signaled in step 403, and the two may be defined in a hierarchical, mutually complementary, or substitutive structure.

[0123] In step 409, the terminal (410) and the base station (420) transmit and / or receive data. In other words, the terminal (410) and the base station (420) can process, transmit, and / or receive data based on the signaling of the control information. For example, when transmitting data, the terminal (410) or the base station (420) can perform at least one of channel encoding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and resource mapping on the information bits. Conversely, when receiving data, the terminal (410) or the base station (420) can perform at least one of signal extraction from resources, waveform demodulation for each antenna, signal arrangement considering layer mapping, constellation demapping, descrambling, and channel decoding. Here, the transmitted data is data related to AI, and may include, for example, data for AI-based operations or data generated by AI-based operations.

[0124] Steps 401 to 409 illustrated with reference to FIG. 4 do not necessarily have to be performed in the order illustrated in FIG. 4, and the order of at least some of the steps may vary. Furthermore, at least some of steps 401 to 409 may be combined into a single step or omitted. That is, the steps illustrated in FIG. 4 may be performed in various modified forms.

[0125]

[0126] 6G communication systems and core implementation technologies of 6G systems

[0127] The 5G system defines various operating bands within FR1 (frequency range 1), which covers 410 MHz to 7125 MHz, and FR2 (frequency range 2), which covers 24,250 MHz to 71,000 MHz. Various frequencies are being discussed as operating bands for the subsequent 6G system, and the use of higher frequencies than 5G systems is also being considered for wider bandwidth and higher transmission speeds. One such band is the THz (terahertz) frequency band, which covers approximately 100 GHz to 10 THz. The THz frequency band is a band that has both the transparency of radio waves and the straightness of light waves, and communications using the THz frequency band are expected to play a transitional role from existing radio-centered communications to lightwave-based communications.

[0128] 6G systems utilizing the THz frequency band have the following goals: i) very high data rates per device, ii) a very large number of connected devices, iii) global connectivity, iv) very low latency, v) reduced energy consumption of battery-free IoT devices, vi) ultra-reliable connectivity, and vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: “intelligent connectivity,” “deep connectivity,” “holographic connectivity,” and “ubiquitous connectivity,” and the 6G system can be designed to satisfy the requirements as shown in [Table 1] below.

[0129] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0130] At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), AI integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security. FIG. 5 illustrates an example of a communication structure that can be provided in a 6G system applicable to the present disclosure. Referring to FIG. 5, the 6G system is expected to have simultaneous wireless communication connectivity that is 50 times higher than that of a 5G wireless communication system. URLLC, a key feature of 5G, is expected to become an even more crucial technology in 6G communications, offering end-to-end latency of less than 1 ms. Furthermore, 6G systems will boast significantly higher volumetric spectral efficiency than the commonly used area spectral efficiency. 6G systems can offer extremely long battery life and advanced battery technologies for energy harvesting, eliminating the need for separate charging for mobile devices in 6G systems. New network characteristics in 6G may include:

[0131] - Satellite integrated network: 6G is expected to integrate with satellites to provide a global mobile network. The integration of terrestrial, satellite, and airborne networks into a single wireless communications system is crucial for 6G.

[0132] Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary, upgrading the wireless evolution from "connected objects" to "connected intelligence." AI can be applied at every stage of the communication process (or at every signal processing step, as described below).

[0133] - Seamless integration of wireless information and energy transfer: 6G wireless networks will transfer power to charge the batteries of devices such as smartphones and sensors. Therefore, wireless information and energy transfer (WIET) will be integrated.

[0134] - Ubiquitous super 3D connectivity: Access to networks and core network functions of drones and very low Earth orbit satellites will create super 3D connectivity in 6G ubiquitous.

[0135] Some general requirements for the new network characteristics of 6G, such as the above, may be as follows:

[0136] - Small cell networks: The concept of small cell networks was introduced to improve received signal quality in cellular systems by increasing throughput, energy efficiency, and spectral efficiency. Consequently, small cell networks are essential for 5G and beyond-5G (5GB) communication systems. Accordingly, 6G communication systems also adopt the characteristics of small cell networks.

[0137] Ultra-dense heterogeneous networks: Ultra-dense heterogeneous networks will be another key feature of 6G communication systems. Multi-tier networks comprised of heterogeneous networks improve overall QoS and reduce costs.

[0138] High-capacity backhaul: Backhaul connections are characterized by high-capacity backhaul networks to support high-volume traffic. High-speed fiber optics and free-space optics (FSO) systems may be potential solutions to this problem.

[0139] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communications is a key feature of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0140] - Softwarization and virtualization: Softwarization and virtualization are two critical features that form the foundation of the design process for 5GB networks to ensure flexibility, reconfigurability, and programmability. Furthermore, billions of devices can be shared on a shared physical infrastructure.

[0141] To satisfy the above-mentioned characteristics, the core implementation technologies of the 6G system may include artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, FSO backhaul network, massive MIMO technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cell-free communication, wireless information and energy transfer (WIET), integration of sensing and communication, integration of access backhaul networks, holographic beamforming, big data analysis, and large intelligent surface (LIS).

[0142] For example, THz communication can be utilized in 6G systems. THz communication is a communication that utilizes a spectrum in a frequency band between 0.3 THz and 3 THz with a corresponding wavelength in the range of 0.1 mm to 1 mm, as shown in FIG. 6. Referring to FIG. 6, the frequency band of THz waves is located in the middle region between the infrared band and the millimeter wave band, and therefore, THz waves can be understood as radio waves with the shortest wavelength and light waves with the longest wavelength. Therefore, THz waves share some of the characteristics of infrared and microwave waves, and specifically, they can simultaneously have the transparency of electromagnetic waves and the straightness of light waves.

[0143]

[0144] Figure 7 illustrates a transmitter structure applicable to the present disclosure.

[0145] Referring to Figure 7, in order to modulate data into an optical signal, an optical source of a laser can be passed through an optical wave guide to change the phase of the signal, etc. At this time, data is loaded by changing the electrical characteristics through a microwave contact, etc. Therefore, the optical modulator output is formed as a modulated waveform.

[0146] Data may be provided from a data signal generator. Here, the data may include various user data, configuration information, control information, etc. transmitted through a channel. Furthermore, the data may include data related to AI-based operations, such as information for configuring an AI model, input / output data for tasks of the AI ​​model, etc. To this end, components related to AI functions (e.g., an AI processing unit) may be included in the data signal generator or may be linked to the data signal generator.

[0147] An optical / electronic converter (O / E converter) can generate THz pulses by optical rectification using a nonlinear crystal, photoelectric conversion using a photoconductive antenna, or emission from a bunch of relativistic electrons. The THz pulse generated in the above manner can have a length in the range of femtoseconds to picoseconds. The optical / electronic converter (O / E converter) performs down conversion by utilizing the nonlinearity of the device.

[0148] Considering the THz spectrum usage, it is likely that multiple contiguous GHz bands will be used for THz systems, either fixed or for mobile services. For an outdoor scenario, the available bandwidth can be categorized based on an oxygen attenuation of 10^2 dB / km in the spectrum up to 1 THz. Accordingly, a framework in which the available bandwidth is divided into multiple band chunks can be considered. As an example of this framework, if the THz pulse length for a single carrier is set to 50 ps, ​​the bandwidth (BW) becomes approximately 20 GHz.

[0149] Effective down-conversion from the infrared band to the THz band depends on how to utilize the nonlinearity of the optical / electrical converter (O / E converter). In other words, to down-convert to the desired THz band, it is necessary to design an O / E converter with the most ideal non-linearity for transferring to the THz band. If an O / E converter that is not suitable for the target frequency band is used, errors in the amplitude and phase of the pulse are likely to occur.

[0150] A THz transmission and reception system can be implemented using a single optical-to-electrical converter in a single-carrier system. Depending on the channel environment, optical-to-electrical converters may be required as many as the number of carriers in a multi-carrier system. This phenomenon will be particularly noticeable in a multi-carrier system that utilizes multiple broadbands according to the aforementioned spectrum usage plan. In this regard, a frame structure for the multi-carrier system may be considered. A signal down-frequency converted based on an optical-to-electrical converter may be transmitted in a specific resource region (e.g., a specific frame). The frequency region of the specific resource region may include multiple chunks. Each chunk may be composed of at least one component carrier (CC).

[0151]

[0152] 6G systems may introduce AI technology. Efficient resource management and optimization are required to maintain connectivity between various services and devices. AI technology may include technologies that perform data analysis, pattern recognition, and predictive modeling using AI / ML (artificial intelligence / machine learning) models. Here, an AI / ML model can be understood as a set of parameter values ​​and / or weight values ​​related to mathematical formulas or algorithms generated through learning to discover patterns in input data or make predictions. To create such an AI / ML model, an AI / ML model learning process is required, which builds an AI / ML model by learning the relationship between inputs and outputs in a data-driven manner. Various learning algorithms, such as supervised learning, unsupervised learning, and reinforcement learning, can be utilized as learning algorithms. To generate output, a user can input specific data into a trained AI / ML model, and the process of obtaining output data by inputting input data into an AI / ML model can be referred to as AI / ML "inference" or "prediction."

[0153] Network control parameters can be obtained as output through AI / ML inference using trained AI / ML models. Users can utilize the output parameter values ​​to improve network efficiency. For example, AI technology can be utilized in various fields, such as wireless network resource allocation, traffic management, fault prediction, and quality of service (QoS) management. In particular, machine learning can efficiently allocate resources even in dynamically changing network environments based on real-time data. Therefore, AI technology can be utilized to provide hyper-connectivity and ultra-low latency.

[0154] At this time, AI / ML inference can be performed based on a combination of various devices. For example, the UE and the network can jointly perform AI / ML inference, and such an AI / ML model can be referred to as a two-sided AI / ML model or a two-sided model. In this case, the UE can perform the first part of the inference first, and the base station can perform the remaining inference, or vice versa. Alternatively, inference can be performed entirely on the UE, and such an AI / ML model can be referred to as a UE-side AI / ML model or a UE-side model.

[0155] Additionally, life cycle management (LCM) can be performed for AI / ML models. Life cycle management can include model training, model deployment, model inference, model monitoring, and model updates. This may require support for data collection, model training, functional / model identification, model delivery / transfer, model inference operations, functional / model selection / activation / deactivation / fallback, functional / model monitoring, model updates, and UE capabilities.

[0156] For example, AI / ML technology can be operated based on a functional framework such as FIG. 8. FIG. 8 illustrates an example of a functional framework for application of AI / ML technology applicable to the present disclosure. First, a data collection function (810) performs data preparation on input data collected from objects (e.g., UE, RAN node, network node, etc.) to generate training data (801), monitoring data (803), and / or inference data (805) including processed input data. A model training function (820), which receives training data (801) from the data collection function (810), performs training on an AI / ML model using the training data (801) and provides a trained / updated model (813) to a model repository (840). The model repository (840) can store and retain the received trained / updated model (813).

[0157] A management function (830) may be used to control AI / ML model training. The management function (830) may control the operation of the AI / ML model or AI / ML functions, or supervise their performance. To this end, the management function (830) may receive monitoring data (830) from the data collection function (810) and inference output (809) from the inference function (840). The management function (830) manages the data received from the data collection function (810) and the inference function (840) so that the inference task can be performed efficiently. That is, the management function (830) may transmit performance feedback or a retraining request (807) to the model training function (820) to improve the inference task. Here, the performance feedback may be used to indicate a learning goal or as a reward for reinforcement learning. Additionally, the management function (830) can transmit management instructions (811) that instruct the inference function (840) to select AI / ML models or AL / ML-based functions to be used, activate / deactivate them, or switch to non-AI / ML operation.

[0158] The inference function (840) generates an inference output (809) by performing inference and / or prediction using the inference data (805) received by the data collection function (810). Here, the inference output (809) refers to the inference output of the AI / ML model used by the inference function (840), and the details of the inference output may vary depending on the use case. The AI / ML model used by the inference function (840) can be controlled by the management function (830). That is, the management function (830) can transmit a model transfer / forward request signal (815) to request a necessary AI / ML model to the model repository function (850), and the model repository function (850) can transmit the corresponding AI / ML model to the inference function (840) via a model transfer / forward signal (817). Therefore, the inference function (840) can perform inference using the AI / ML model (817) according to the received management instruction (811).

[0159] Additionally, the management function (830) may trigger or perform a designated task / action based on the inference output (809). Accordingly, the management function (830) may trigger a task / action for another entity (e.g., at least one UE, at least one RAN node, at least one network node, etc.) or for itself. Any one of the functions exemplified in FIG. 8 described above may be performed by two or more entities, including the RAN, the network node, the network operator's OAM, or the UE, in collaboration. This may be referred to as a split AI operation.

[0160] Not all of the functions (810 to 850) illustrated in FIG. 8 need to be used to utilize the AI / ML model, and the method of combining them is not limited to a specific method. Accordingly, the functions (810 to 850) may be operated in an integrated manner, or some functions may be omitted. Furthermore, the functions (810 to 850) illustrated in FIG. 8 are not necessarily limited to being implemented as separate devices or apparatuses. For example, some or all of the functions (810 to 850) may be included in the processor (202) of FIG. 2. Furthermore, the model storage function (850) may be included in the memory (204) of FIG. 2.

[0161]

[0162] FIG. 9 illustrates an example of a procedure for utilizing an AI model applicable to the present disclosure. FIG. 9 illustrates a case where a model training function (820) is included in a network node and a model inference function (840) is included in a RAN node. Referring to FIG. 9, in step 1, RAN node 1 and RAN node 2 transmit input data (e.g., training data) for training an AI model to the network node. Here, RAN node 1 and RAN node 2 may transmit data collected from the UE (e.g., measurements of the UE related to RSRP, RSRQ, SINR of the serving cell and neighboring cells, the UE's position, speed, etc.) together to the network node. In step 2, the network node trains the AI ​​model using the received training data. In step 3, the network node distributes / updates the AI ​​model to RAN node 1 and / or RAN node 2. RAN node 1 and / or RAN node 2 may also continue model training based on the received AI model. In this procedure, it is assumed that the AI ​​model is deployed / updated only to RAN node 1. In step 4, RAN node 1 receives input data (e.g., inference data) for AI model inference from UE and RAN node 2. In step 5, RAN node 1 performs AI model-based inference using the received inference data to generate output data (e.g., prediction or decision). In step 6, if applicable, RAN node 1 may transmit model performance feedback to network nodes. In step 7, RAN node 1, RAN node 2, and UE (or 'RAN node 1 and UE', or 'RAN node 1 and RAN node 2') perform actions based on the output data. For example, in case of load balancing operation, the UE may move from RAN node 1 to RAN node 2. In step 8, RAN node 1 and RAN node 2 transmit feedback information to network nodes.

[0163] Network nodes can manage AI models based on feedback information regarding the AI ​​model's inference results. For example, the network node can perform additional training on the AI ​​model or generate additional information about the AI ​​model (e.g., performance information, accuracy information, etc.). If additional training is performed on the AI ​​model, the network node can distribute the updated AI model to RAN node 1.

[0164] As described with reference to Figure 9, model training can be performed by network nodes, and inference using the model can be performed by RAN node 1. In other words, the model training and inference functions can be distributed. Typically, model training requires significant computational resources because it utilizes large amounts of data and complex algorithms for optimization. In contrast, inference, which uses a trained model to derive conclusions about new data, requires relatively fewer computational resources compared to model training. Therefore, using the procedure of Figure 9, model training can be performed through network nodes when the computational resources of the UE or RAN node are insufficient. Furthermore, security can be ensured for the AI ​​model because the AI ​​model is not disclosed to the UE.

[0165] FIG. 9 illustrates a case where a model training function (820) is included in a network node and a model inference function (840) is included in a RAN node, but the present disclosure is not limited thereto. For example, if the computational resources of the RAN node are sufficient, both the model training function (820) and the model inference function (840) may be included in RAN node 1. In this case, RAN node 1 receives training data for training an AI model from the UE and RAN node 2. RAN node 1 trains the AI ​​model using the received training data. Thereafter, RAN node 1 receives inference data for AI model inference from the UE and RAN node 2. RAN node 1 performs inference based on the AI ​​model using the received inference data to generate output data. Based on the output data, the UE, RAN node 1, and RAN node 2 may perform operations related to communication (e.g., handover, cell change). Thereafter, the UE and RAN node 2 may transmit feedback regarding the operations to RAN node 1. Therefore, RAN node 1 can learn the AI ​​model and update its own AI model using feedback information regarding the AI ​​model's inference results. According to the aforementioned method, signaling with the network is not required for AI model learning and inference, thereby reducing network load and delays until the AI ​​model is trained or inference results are received. Furthermore, since the UE performs inference using the AI ​​model, its personal information is not transmitted to network nodes, etc., thereby enhancing the security of personal information.

[0166] As another example, the model training function (820) may be included in the RAN node, and the model inference function (840) may be included in the UE. The RAN node receives training data for training an AI model from the UE, and trains the AI ​​model using the received training data. The RAN node distributes the trained AI model to the UE. The UE may perform inference based on the received AI model to generate output data. At this time, the data for inference may be received from the RAN node, or the UE may use data acquired on its own. The UE and the RAN node may perform communication-related operations based on the output data generated by inference. Thereafter, the UE may transmit feedback regarding the operation to the RAN node. Therefore, the RAN node may train the AI ​​model and distribute the updated AI model to the UE through feedback information regarding the inference result of the AI ​​model. According to the above-described method, the model training function (820) may be included in the RAN node, and the model inference function (840) may be included in the UE to perform inference, thereby reducing the load on the RAN node. Additionally, if the UE uses data acquired on its own to make inferences, even if the UE loses connection with the RAN node after receiving the AI ​​model, the UE can continue to infer the distributed AI model and perform operations based on the inference results.

[0167] According to the framework and procedures described above, an AI model can be trained and utilized in a wireless communication system. The model training function (820) and the model inference function (840) can be combined in various ways and are not necessarily limited to the case of FIG. 9. In the framework and procedures described above, various types of data, such as input data, training data, and inference data, are introduced, and the specific content of the data described above may vary depending on the task for which the AI ​​model is utilized. For example, information used in various embodiments of the present disclosure described below may be included in the data described above.

[0168]

[0169] Figure 10 illustrates an AI technology-based communication procedure applicable to the present disclosure. The detailed procedures illustrated in Figure 10 can be combined with various embodiments of the present disclosure described below. For example, data generated according to various embodiments of the present disclosure can be used for operations (e.g., configuration, training, inference, and / or data transmission / reception) in at least one of the detailed procedures illustrated in Figure 10. As another example, the results of the inference illustrated in Figure 10 can be used to transmit and / or receive data according to various embodiments of the present disclosure.

[0170] Referring to FIG. 10, in step S1001, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs an initial access procedure. For example, in this step, at least one of an initial cell search operation, a system information acquisition operation, a random access operation, and a registration operation may be performed. In step S1003, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs a configuration procedure. Through the configuration procedure, parameters, resources, connections, and / or entities necessary for performing subsequent procedures in layers between the UE (1010) and the RAN node (1020) and / or in at least one layer between the UE (1010) and the network node (1030) may be determined and / or created. In this case, the configuration procedure may be performed based on information, status, and / or characteristics of an AI model used for subsequent training and inference.

[0171] In step S1005, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs a model training procedure. At least one of the UE (1010), the RAN node (1020), and the network node (1030) may collect training data and perform learning using the training data. For example, the model training procedure may be performed as described with reference to FIG. 9. If an offline-trained model is used, this step may be omitted.

[0172] In step S1007, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs a task using the trained model. That is, the task may be performed based on the results of inference and / or prediction using the trained model. For example, the task may be a procedure belonging to a communication protocol, and may be a preparatory operation for subsequent data transmission and / or reception, or may be related to data transmission and / or reception, or may be related to data processing (e.g., encoding, decoding, etc.).

[0173] In step S1009, at least one of the UE (1010), the RAN node (1020), and the network node (1030) transmits and / or receives data. At this time, the result of the task performed in step 1007 may be used. In some cases, the task performed in step 1007 may include transmitting and / or receiving data, in which case this step may be omitted as it is part of step 1007.

[0174]

[0175] Specific embodiments of the present disclosure

[0176] This disclosure proposes a procedure for supporting multiple quality of service (QoS) flows based on dynamic lattice transformations based on entanglement percolation in quantum communications. The method proposed in this disclosure can be implemented through an entanglement percolation procedure for forming or distributing remote entanglement between two distant transmitting and receiving nodes. Furthermore, this disclosure provides that different QoS flows can have different QoS characteristics.

[0177] We propose a procedure for transforming a network lattice structure to more efficiently perform entanglement penetration for multiple transmit and receive flows with different QoS characteristics. The network lattice structure can be configured with non-identical sub-networks with different entanglement penetration performances, enabling different QoS characteristics.

[0178] Here, the QoS characteristics can be configured by at least one of resource type (e.g., non-GBR, GBR, delay-critical GBR), priority level, packet delay budget, packet error rate, average window, and maximum data burst volume. The QoS characteristics to be used for communication can be defined in advance, and the characteristics can be indicated using an index. For example, a set of QoS characteristics can be referred to as a QoS class, and a mapping relationship between an indicator of an OoS class (QoS class identifier, QCI) and the QoS characteristics can be defined in advance. As another example, a mapping relationship between a 5QI (5G QoS identifier) ​​and QoS characteristics can be defined in advance, and the QoS characteristics can be indicated through the 5QI.

[0179] Qubits in an entangled state can be used to transmit information between nodes. In quantum communication, entangled qubits can be used to prevent eavesdropping or information leakage. Furthermore, if an entangled state can be created between distant nodes, quantum communication between them can be achieved using that entangled state. Specifically, entangled states enable the implementation of security protocols such as quantum key distribution (QKD).

[0180] Quantum communication using entangled qubits can encounter problems such as noise and decoherence. Quantum qubits can easily change their state under external influence, potentially resulting in information loss. Therefore, noise and decoherence hinder reliable quantum communication and can occur even between two nodes far apart. Therefore, a method is needed to maintain a stable quantum entanglement state by minimizing noise and decoherence.

[0181] The abbreviations used in this disclosure are as follows.

[0182] - NTI: Network Topology Information

[0183] - NCI: Network Configuration Information

[0184] - NCM: Network Configuration Mode

[0185] - SN: sub-network

[0186] - LOCC: local operation and classical communication

[0187] - E2E: end-to-end

[0188] - qUE: Quantum User Equipment

[0189] - qNB: quantum node B

[0190] - LCI: Link Connectivity Information

[0191] - SCP: single conversion probability

[0192] - QoS: Quality of Service

[0193] The definitions of terms used in this disclosure are as follows.

[0194] - Node: A device, terminal, or entity that constitutes a network. In a quantum network, this may refer to a quantum device, quantum terminal, or quantum entity.

[0195] - Link: refers to the connection between neighboring nodes. In quantum networks, it refers to the entangled state shared between neighboring nodes (i.e., link entanglement).

[0196] - Link connectivity: This refers to the probability of forming a link connecting two neighboring nodes. In quantum networks, this refers to the probability of successfully forming link entanglement in a maximally entangled state between neighboring nodes.

[0197] One of the key steps in building a global quantum network is the process of creating remote entanglement between any two distant nodes within the network. According to percolation theory, if the degree of connectivity among the links forming the network exceeds a percolation threshold, a unique cluster of infinite size exists within the network with a probability of 1.

[0198] Here, the link connectivity can be expressed as a value between 0 and 1, and can correspond to the amount of entanglement contained in the link entanglement shared between two neighboring nodes through a quantum direct channel. For example, the link connectivity when the link entanglement is in a maximally entangled state can be expressed as 1, and the link connectivity when it is in a separable state can be expressed as 0. The penetration threshold can mean the minimum link connectivity that each link entanglement must have to successfully form a remote entanglement between any two distant nodes in the network, or the minimum value that the average link connectivity of all link entanglements in the network must satisfy. The penetration threshold can appear differently depending on the structure of the network topology.

[0199] If the link connectivity does not exceed the penetration threshold, the probability of a cluster of infinite size existing in the network becomes zero. This means that even if network resources are used infinitely, it may become impossible to form a path connecting two distant nodes. For example, the network topology structure may be formed as shown in Figures 11a through 11d.

[0200] Figures 11a to 11d illustrate examples of network topologies in the form of lattice graphs according to one embodiment of the present disclosure. Figure 11a illustrates a square lattice graph, Figure 11b illustrates a triangular lattice graph, Figure 11c illustrates a hexagonal lattice graph, and Figure 11d illustrates a Kagome lattice graph. In Figures 11a to 11d, connection links are represented by lines connecting each node. The two edges of a connection link represent quantum pairs that exist in an entangled state. That is, entanglement can be formed between one node and surrounding nodes. For example, in a square lattice structure as shown in Figure 11a, one node can form connection links with four surrounding nodes. It is also possible to construct a subnetwork using only some nodes in the entire lattice graph. For example, in the case of using a honeycomb lattice structure as shown in Figure 11c, a subnetwork can be constructed using only some of the nodes existing in the network as shown in Figure 11c.

[0201] [Table 2] below shows the penetration thresholds from the perspective of line penetration for the grid networks of FIGS. 11a to 11d.

[0202] LatticePercolation thresholdSquare Triangular Honeycomb Kagome0.5244

[0203] One of the key performance metrics in percolation theory is the percolation probability. The percolation probability represents the probability that a random node will be included within the aforementioned infinite-sized cluster. Therefore, this probability is zero in regions where the link connectivity is below the percolation threshold, and it becomes greater than zero when the link connectivity is greater than the percolation threshold. Like the percolation threshold, the percolation probability can be determined differently depending on the network structure. The percolation probability for the lattice networks of Figures 11a to 11d can be expressed as shown in [Table 3] below.

[0204] LatticeA few terms in series expansions about of ( )Square Triangular Honeycomb Kagome

[0205] Referring to [Table 3], the penetration probability The link connection diagram is based on the grid structure. It can be confirmed that it is determined as a function of . As shown in Fig. 12, it can be seen that the higher the link connectivity, the higher the penetration probability. The application of penetration theory to the problem of distributing remote entanglement between two nodes far apart in a quantum network can be referred to as entanglement penetration. Below, the interpretation of the physical meaning of link connectivity and penetration threshold in the entanglement distribution problem is described. In a quantum network, a node can be a quantum device that constitutes a quantum network, and a link can mean a wired or wireless quantum direct channel between quantum nodes. In this case, link connectivity can mean the amount of entanglement of the quantum direct channel between two neighboring nodes. Here, the amount of entanglement can correspond to the amount of entanglement of the multi-qubit state shared by two neighboring nodes through the link. In addition, the amount of entanglement can also mean the probability of successfully forming link entanglement through the link. Link connectivity is expressed as a value between 0 and 1. In a quantum network, link connectivity failing to exceed the penetration threshold could indicate increased channel loss in the quantum direct channel constituting each link, reducing the probability of successful quantum state transmission. Alternatively, link connectivity failing to exceed the penetration threshold could indicate increased channel noise, reducing the degree of entanglement of the multi-qubit state shared across the channel. If link connectivity fails to exceed the penetration threshold, processes such as retransmission or entanglement refinement are required to raise the connectivity of each link above the penetration threshold. These processes can consume significant quantum channel resources. Furthermore, supporting multiple flows for multiple transmitting and receiving pairs can be a critical requirement when distributing remote entanglement between two distant nodes in a quantum network.

[0206] In a communication environment supporting multiple transmit and receive flows, multiple transmit and receive flows with different QoS characteristics may exist. In this case, an entanglement penetration strategy is needed that supports entanglement distribution performance corresponding to each QoS characteristic while simultaneously maintaining high network resource efficiency.

[0207] Figure 13 illustrates an example of a honeycomb-lattice-based subnetwork configuration method according to one embodiment of the present disclosure. Referring to Figure 13, multiple flows can be efficiently supported regardless of the geographical correlation between multiple transmit / receive pairs. As shown in Figure 13, the entire network, which is a triangular lattice, can be divided into three honeycomb-lattice subnetworks and operated. Since the three subnetworks with the honeycomb-lattice structure overlap in a multi-layered manner within the same area, simultaneous entanglement distribution procedures can be supported even for two transmit / receive pairs where flows intersect. At this time, transmit / receive flows can be supported in each subnetwork, and the entanglement distribution process can be supported simultaneously for the three flows. However, because the three subnetworks have the same structure, they can have the same entanglement penetration performance. Therefore, when subnetworks are configured based on the same lattice structure, there is an advantage in terms of fairness in resource distribution for multiple flows, but there is a limitation in that it is difficult to support heterogeneous OoS characteristics.

[0208] Below, a network structure and terminology related to the network structure for supporting heterogeneous QoS characteristics are described. In the present disclosure, a node constituting a network may be a device included in a quantum network (hereinafter referred to as a "quantum device"). In the present disclosure, a quantum device may be referred to as a quantum terminal, a quantum device, a quantum user equipment, or other terms having equivalent technical meanings. In addition, a node may be a mobile device or a device existing in a fixed location. In addition, a node may be a quantum terminal performing a function similar to a terminal in a wireless network, or may be referred to as a quantum base station performing a function similar to a base station.

[0209] Links forming a network can represent multi-qubit states shared between neighboring nodes, i.e., link entanglement states. Links can be formed via wired or wireless quantum direct channels, or via these quantum direct channels.

[0210] In the present disclosure, the quantum network may include a separate entity that functions as a base station or manager. Therefore, at least one node among the multiple nodes included in the quantum network may perform the base station or manager role. The node that functions as a manager may be referred to as a control node or a control device.

[0211] The control device and nodes can promise multiple network configuration information during the initial network formation phase and then monitor the link connectivity of the links forming the network to change the network configuration to an appropriate topology. The network configuration can be set through a network configuration mode that can indicate at least one subnetwork. Here, the network configuration mode can be determined based on a percolation threshold value related to bond percolation in percolation theory.

[0212] Here, the network configuration mode refers to a network structure that performs quantum communication using network topology, which is a connection method of elements of a quantum network (e.g., nodes, links), and multiple network configuration modes can be set.

[0213] To configure a dynamic network, nodes belonging to the network can monitor link status. Based on the link status monitored by the nodes, a network configuration mode appropriate to the current link status of the network can be selected from among multiple network configuration modes. The network configuration information may include network topology information for multiple network configuration modes and role information of each node for performing an entanglement infiltration procedure in the corresponding mode. Here, the entanglement infiltration procedure refers to a procedure for establishing a maximally entangled state between any two nodes belonging to the network based on infiltration theory. The role information of each node may be referred to as an infiltration mode, an infiltration execution mode, an operation mode, or other terms having equivalent technical meanings.

[0214] In order to support multiple QoS characteristics, multiple sub-networks can be configured within at least one network configuration mode, and the operation mode of nodes can be dynamically configured for each of the sub-networks.

[0215] In this disclosure, the entire network refers to all nodes and links within the quantum network. Subnetworks can be defined using some of the components within the entire network. The quantum network can indicate some of the definable subnetworks, and can use the network configuration mode to indicate a set of subnetworks appropriate for the current network link status.

[0216] The triangular lattice is an Archimedean lattice with a very high entanglement penetration rate. Therefore, to support high QoS performance, a method that applies an optimal LOCC strategy for 2-hop segments while maintaining the structural advantages of the triangular lattice can be used.

[0217] FIG. 14 illustrates an example of a Kagome-based network configuration method according to one embodiment of the present disclosure. In FIG. 14, the entire network can be configured as a triangular lattice, as shown in the network structure on the left side of FIG. 14. The entire network in the triangular lattice structure can be configured as a first sub-network in the triangular lattice structure, consisting of links with doubled lengths (i.e., links consisting of 2-hop segments), and a second sub-network in the Kagome form, consisting of the remaining links. The first sub-network is indicated by the solid line in the right side of FIG. 14, and the second sub-network is indicated by the dotted line in the right side. The Kagome lattice structure, indicated by the dotted line, has entanglement penetration performance between that of the square lattice structure and the honeycomb lattice structure. The second sub-network inherits the performance of the Kagome lattice without an enhanced LOCC strategy, so it can be used as a sub-network with lower QoS performance. However, in terms of overall network resource efficiency, research into a LOCC strategy that is more advanced than that of the Kagome lattice structure is needed.

[0218] The present disclosure proposes a method for more efficiently supporting an entanglement distribution procedure for transmission and reception flows with heterogeneous QoS characteristics in an environment where multiple transmission and reception flows with different QoS characteristics exist. Specifically, the present disclosure proposes a dynamic lattice transformation-based entanglement penetration method that can further improve network resource efficiency when a network is composed of heterogeneous subnetworks with different entanglement penetration performances. In the present disclosure, the dynamic lattice transformation-based entanglement penetration method means that the LOCC strategy performed by each node in the subnetwork can be dynamically allocated for each entanglement penetration operation.

[0219] Figures 15a and 15b illustrate examples of an entanglement infiltration technique based on dynamic lattice transformation according to an embodiment of the present disclosure. Figure 15a illustrates a sub-network of a triangular lattice structure and a sub-network of a kagome lattice structure determined based on the structure of a basic network based on a triangular lattice, and Figure 15b illustrates sub-network structures changed based on dynamic lattice transformation. In Figure 15a, circles represent quantum states possessed by each node. Each node can possess multiple quantum states, and six of these quantum states can be used. In Figure 15a, each node can be connected to neighboring nodes using six links (e.g., thick solid lines and dotted lines). In this case, the thick solid lines can be used in the first sub-network, and the dotted lines can be used in the second sub-network. As a result, the first sub-network composed of the thick solid lines can have a triangular lattice structure, and the second sub-network composed of the dotted lines can have a kagome lattice structure. As shown in Figure 15a, the control node can define a network configuration mode that divides the links constituting the basic network into two sets that do not share common elements, and defines each of the two sets as a subnetwork. Therefore, nodes can perform an entanglement infiltration procedure using two separate subnetworks in the basic network in the form of a triangular lattice. To establish the network configuration mode, nodes belonging to the network can establish a strategy for converting the lattice structure in the two subnetworks. Thereafter, the second subnetwork, which is a Kagome lattice structure, can be operated as a square lattice through a lattice conversion strategy as shown in Figure 15b.

[0220] For a specific subnetwork, the operating mode of each node can be determined as one of the vertex, repeater, and excluded modes. Here, the operating mode can be referred to as penetration mode, penetration execution mode, and other terms with equivalent technical meaning. At this time, a node classified as vertex or repeater mode for any subnetwork is a node included in the subnetwork, and a node classified as excluded mode means that it is not included in the subnetwork. Not all modes need to be included, and only some of them can be used, or other modes can be added and used. For example, as shown in FIG. 15b, nodes within a single subnetwork can be set to either vertex mode or repeater mode. As shown in FIG. 15b, the connection lines of the subnetworks can be configured as a 2-hop segment consisting of three nodes, as shown in FIG. 17. The 2-hop segment will be described in detail later.

[0221] Even when subnetworks are established, the operating mode of each node corresponding to the subnetwork can be set to fixed, semi-static, or dynamic, and these settings can be set differently for each subnetwork. For example, in the first subnetwork, the operating mode of each node can be set to fixed or semi-static, and in the second subnetwork, the operating mode of each node can be set to dynamic.

[0222] Since the first subnetwork is set to a fixed or semi-static operation mode, the lattice structure of the first subnetwork does not change. Therefore, the links of the first subnetwork indicated by thick solid lines (indicated as Link for SN. 1 in Fig. 15b) are also indicated by a triangular lattice structure with thick solid lines in Figs. 15a and 15b. In the first subnetwork of Fig. 15b, nodes operating in relay mode perform Bell state measurements using quantum pairs included in the ellipses indicated by the solid lines in Fig. 15a. Nodes not included in the ellipses indicated by the solid lines in Fig. 15a correspond to nodes operating in vertex mode. Since the entanglement infiltration mode of each node in the first subnetwork is fixed to either a vertex or a repeater, the LOCC process that each node must perform can also be fixedly assigned accordingly. Therefore, an entanglement infiltration method based on a semi-static lattice transformation can be used.

[0223] Here, the term "semi-static" refers to a state in which, once one element is determined, other elements are automatically or partially determined based on that determined element. In other words, it refers to a relationship in which, once one element is determined, the determined element influences the values ​​of other elements. Therefore, the semi-static setting of the operating modes of network nodes means that the operating modes are determined dependently by the subnetwork. Therefore, by utilizing the semi-statically set operating modes, a node designated by a subnetwork can be aware of its own operating mode without additional signaling regarding the operating mode. The correspondence between subnetworks and operating modes can be provided to network nodes in advance.

[0224] As described above in Fig. 12, even in the Kagome lattice structure, entanglement penetration performance that is almost close to that of a square lattice can be achieved. However, since the second sub-network with the Kagome lattice structure has a dynamically set operation mode, the Kagome lattice structure can be used as a modified structure. Therefore, a higher entanglement penetration efficiency can be achieved through an optimal LOCC strategy for an additional 2-hop segment. Fig. 15b is a diagram showing an example in which the LOCC strategy for a 2-hop segment is maximally applied in the second sub-network with the Kagome lattice structure. As an example, the second sub-network with the Kagome lattice structure can be modified into a square lattice structure composed of the links indicated by the dotted lines in Fig. 15b. In the second sub-network modified into the square lattice structure, nodes operating in repeater mode (hereinafter, repeater nodes) are located at the center of a bond in the square lattice graph, and two link hops can be converted into a single bond. To this end, the relay node can perform a Bell state measurement. Nodes operating in vertex mode adjacent to the relay node (hereinafter referred to as vertex nodes) can perform a LOCC procedure to transform the new bonds obtained after the grid transformation into a maximally entangled state based on the Bell state measurement results of the relay node.

[0225] A node operating in relay mode in the second subnetwork can perform Bell state measurements using the quantum pairs included in the dotted oval in Fig. 15a. Therefore, a two-hop segment can be formed through Bell state measurements, and the second subnetwork in the Kagome lattice structure can be converted into a network structure in the square lattice structure, as indicated by the dotted line in Fig. 15b, and used. Furthermore, some links in the second subnetwork in the Kagome lattice structure, such as the links indicated by the solid lines, may not be used. Therefore, by converting the Kagome lattice structure to a square lattice structure, fewer resources can be consumed. Since the square lattice structure has higher entanglement penetration performance than the Kagome lattice structure, using the network structure in Fig. 15b can achieve higher network performance with less resource consumption. Specifically, by utilizing the structure of the second subnetwork converted into the rectangular lattice structure of Fig. 15b, only 66.67% of the total network resources can be utilized based on the optimal LOCC strategy for two-hop segments consisting of two link hops. Therefore, a more efficient rectangular lattice network can be formed. Meanwhile, the method for converting a Kagome lattice to a rectangular lattice, as shown in Fig. 15b, can be determined differently depending on the arrangement of vertex nodes and relay nodes.

[0226] FIGS. 16A and 16B illustrate another example of an entanglement infiltration technique based on dynamic lattice transformation according to an embodiment of the present disclosure. In FIGS. 16A and 16B , it is assumed that the sub-networks are configured in the same manner as in FIGS. 15A and 15B , with a first sub-network having a triangular lattice structure and a second sub-network having a Kagome lattice structure. Accordingly, in FIG. 16A , each node can be connected to neighboring nodes using six links (e.g., thick solid lines and dotted lines). Similarly to FIGS. 15A and 15B , the links in the thick solid lines in FIGS. 16A and 16B are used in the first sub-network, and the links in the dotted lines are used in the second sub-network. Therefore, the first sub-network composed of the links in the thick solid lines can have a triangular lattice structure, and the second sub-network composed of the links in the dotted lines can have a Kagome lattice structure. Additionally, it is assumed that the operation mode of the first sub-network is set to be fixed or semi-static, and the operation mode of the second sub-network is set to be dynamic.

[0227] At this time, the square lattice structure into which the second sub-network, which is the Kagome lattice, is converted in FIGS. 16a and 16b can be implemented differently from the square lattice structure converted in FIGS. 15a and 15b. That is, as in FIG. 16b, it can be converted into a square lattice structure based on vertex nodes and relay nodes that are set differently from FIG. 15b. Accordingly, a LOCC strategy different from the LOCC strategy of FIG. 15b is instructed to each node. Accordingly, the ellipse indicated by the dotted line in FIG. 16a is displayed in a different location from the ellipse indicated by the dotted line in FIG. 15a, and the links indicated by the dotted line used in the second sub-network in FIGS. 15b and 16b are composed of different links. Similarly, the locations of the unused links indicated by the solid line in FIG. 16b are also configured differently. That is, the second sub-network having the Kagome lattice structure can be changed to a square lattice structure composed of links indicated by solid lines in Fig. 15b, or a square lattice structure composed of links indicated by solid lines in Fig. 16b. In this way, when two or more network resource configurations and LOCC strategy configurations for lattice transformation can be set in one sub-network, a method of dynamically assigning the operation mode for performing entanglement of each node, rather than fixally assigning it, can be used for each entanglement infiltration. Here, the meaning of dynamically is that multiple operation modes are defined in one sub-network, and which operation mode a node will perform is dynamically set. In the present disclosure, dynamically assigning the operation mode for each entanglement infiltration is defined as an entanglement infiltration technique based on dynamic lattice transformation. By using an entanglement infiltration technique based on dynamic lattice transformation, the load of the network is evenly distributed, and an appropriate network structure corresponding to the transmission and reception flows that requested entanglement distribution can be used for the entanglement infiltration process.

[0228] FIG. 17 illustrates an example of a 2-hop segment according to an embodiment of the present disclosure. Referring to FIG. 17, nodes A (1701) and B (1702) may operate in vertex mode, and node R (1703) may operate in relay mode. The following describes a specific procedure for forming a 2-hop segment. In FIG. 17, node R (1703), which is a relay node, may be set as an intermediate node of the 2-hop segment. The 2-hop segment means that the link between node A (1701) and node R (1703) and the link between node R (1703) and node B (1702) are integrated into a single link.

[0229] In the first step, neighboring nodes share one qubit selected from a pair of qubits in an entangled state. Therefore, nodes A (1701) and R (1703) each have a qubit in a quantum entangled state. and qubits can be divided. Also, node B (1702) and node R (1703) are each qubits in a quantum entangled state. and qubits can share the entanglement resource shared between node A (1701) and node R (1703). and shared entanglement resources between node R (1703) and node B (1702). If is a partially entangled pure state, then and can be expressed as a state like [Mathematical Formula 1].

[0230]

[0231] In [Equation 1], and Is It refers to the Schmidt coefficients of and Is It means the Schmidt coefficient of .

[0232] Nodes A (1701), B (1702), and R (1703) can each know the Schmidt coefficients for the two-qubit entangled states they share with their neighboring nodes.

[0233] In the second step, the relay node transmits its own qubits , qubit Bell state measurement is performed on the ZZ basis. This process is for qubits , qubit , qubit , qubit It can be expressed as in [Mathematical Formula 2] below.

[0234]

[0235] [Mathematical formula 2] , , , It can be expressed as [Mathematical Formula 3] below using .

[0236]

[0237] Therefore, the measurement statistics and post-measurement status for the bell state measurement of the relay node can be expressed as shown in [Table 4] below.

[0238] Bell State Measurement Result Probability Qubit , After measurement of the condition

[0239] A relay node can transmit its Bell state measurement results to one of its adjacent vertex nodes via classical channel transmission. For convenience of explanation, it is assumed below that Node R (1703) transmits to Node A (1701). However, it can also transmit to Node B (1702), and subsequent procedures can be performed by Node B (1702). In this case, the Bell state measurement results can be transmitted via classical channel.

[0240] In the third step, the vertex node that received the Bell state measurement result performs a measurement to transform the remaining qubits that were not measured into a maximally entangled state. Therefore, node A (1701) and qubits By performing a measurement, the qubits can be converted into a maximally entangled state. At this time, the qubit and qubits After measuring the status of ( ) then node A (1701) is a qubit The measurement to be performed is a measurement operator as shown in [Mathematical Formula 4] below. and can be expressed as

[0241]

[0242] In [Equation 4], and is a measurement operator and It means the design parameters.

[0243] Design parameters here and can be set as shown in [Table 5] below.

[0244] Measurement operator for the bell state measurement result of the repeater , Design parameters of , Qubit if successful , state of

[0245] Node A (1701) is used to design a measurement operator from Node B (1702) or Node R (1703). Schmidt coefficient of and Node A (1701) can receive information from qubits and qubits A procedure is performed to convert the entangled state between nodes into a maximally entangled state. If node A (1701) The transformation to the maximally entangled state obtained by the measurement results is judged to be successful, If the measurement result is obtained, it can be judged that the transformation to the maximally entangled state has failed. Here, the probability of being judged as successful is It could be.

[0246] Through the aforementioned Bell state measurement and LOCC procedures, new connections, such as two-hop segments, can be created, and the entire triangular lattice network can be transformed into subnetworks of a rectangular lattice based on the new connectivity. Furthermore, when subnetworks do not have common elements, as in the structures of FIGS. 15b and 16b, the entanglement infiltration process can be performed on each subnetwork. Therefore, when the subnetworks of FIGS. 15b and 16b are utilized, the entanglement infiltration process can be performed simultaneously on multiple pairs of transmitting and receiving nodes, providing the advantage of this process.

[0247] Fig. 18 illustrates an example of a procedure in which a first node performs entanglement penetration according to an embodiment of the present disclosure. Fig. 18 illustrates a method performed by a device included in a quantum network (e.g., a node of Fig. 13, a node of Fig. 15, a node of Fig. 16, and a node A (1701), a node B (1702), and a node R (1703) of Fig. 17). In the description referring to Fig. 18, an operating subject is referred to as a first node, and the first node is a device included in the quantum network, which may function as a transmitting node, a receiving node, or an intermediate node. In Fig. 18, a control node is a device that controls nodes included in the quantum network, and may be a node included in the quantum network or an external device.

[0248] Referring to FIG. 18, in step S1801, the first node performs an initial connection procedure. The first node can be connected to other nodes through a classical channel or a quantum channel through the initial connection procedure. To perform the initial connection procedure, the first node can detect a synchronization signal and receive system information. The first node can transmit a signal for initial connection (e.g., a random access preamble) to the control node and receive a response signal for the signal for initial connection from the control node. Here, the system information can include information related to the properties or characteristics of the control node for performing quantum communication. The system information can be transmitted through a master information block (MIB) and a system information block (SIB).

[0249] In step S1803, the first node receives information regarding a network configuration from the control node. For example, the information regarding the network configuration may include configuration information related to bandwidth, channels, etc. for communication. According to various embodiments of the present invention, the information regarding the network configuration may include information indicating a specific network configuration mode to be used in quantum communication. The first node can identify the currently used network configuration mode through the information indicating the network configuration mode. If multiple network configuration modes can be used, the information regarding the network configuration may indicate one selected from among the currently operable network configuration modes. For this purpose, at least one network configuration mode may be defined, and detailed information regarding at least one of the network configuration modes may be conveyed via a message specifically designed to convey information regarding the network configuration (e.g., a network configuration information (NCI) message).

[0250] In step S1805, the first node performs a path establishment procedure. Through the path establishment procedure, a path related to a transmission / reception flow between a transmitting node and a receiving node can be determined. The path related to the transmission / reception flow can be composed of nodes included in the network, links, or multi-hop segments generated through a LOCC procedure. Remote entanglement between the transmitting node and the receiving node can be formed through the determined path. For example, the path between the transmitting node and the receiving node can be determined as a path using the 2-hop segments of FIG. 17. Nodes can perform a LOCC procedure to determine whether the multi-hop segment can be formed in a maximally entangled state. The LOCC procedure can include a measurement procedure and a reporting procedure. Here, a maximally entangled multi-hop segment refers to a segment in which the states of quantum qubits, one at each end of the multi-hop segment, are successfully converted into a maximally entangled state.

[0251] In step S1807, the first node performs an entanglement exchange procedure based on the determined path. Information regarding the path determined through the path setting procedure may be transmitted from the control node to the first node. If the first node is included in the determined path, the first node may perform a multi-hop entanglement exchange procedure. Remote entanglement may be formed between the transmitting node and the receiving node using multiple remote entangled states.

[0252] Here, the multi-hop entanglement exchange procedure may be a LOCC procedure including a step in which intermediate nodes on the path perform Bell state measurements, a step in which the transmitting node and the receiving node involved in the entanglement distribution request report the measurement results, and a step in which the transmitting node and the receiving node perform local operations to transform the end-to-end entanglement into a promised state among the four Bell states based on the Bell state measurement results of the intermediate nodes.

[0253] FIG. 19 illustrates an example of a procedure in which a control node performs entanglement penetration according to an embodiment of the present disclosure. FIG. 19 illustrates a method performed by a device controlling a quantum network. In the description referring to FIG. 19, an operating entity is referred to as a control node, and the control node may be one of the nodes constituting the quantum network (e.g., the node of FIG. 13, the node of FIG. 15, and the node A (1701), node B (1702), and node R (1703) of FIG. 17), or may refer to a separate control device distinct from the nodes of the quantum network. In FIG. 19, the control node may perform the role of a network core or a base station.

[0254] Referring to FIG. 19, in step S1901, the control node performs an initial connection procedure. The control node can connect to nodes included in the network via a classical channel through the initial connection procedure. To perform the initial connection procedure, the control node can transmit system information to nodes included in the network, receive signals for initial connection from the nodes, and transmit a response signal to the signals for initial connection. Here, the system information can include information related to the properties or characteristics of the control node for performing quantum communication. The system information can be transmitted through a master information block (MIB) and a system information block (SIB).

[0255] In step S1903, the control node transmits network configuration information to the first node. The network configuration information may include information indicating a network configuration mode to be used for quantum communication. Here, the network configuration mode refers to a network structure that performs quantum communication using network topology, which is a connection method of elements (e.g., nodes and links) of a quantum network. To utilize a semi-static lattice transformation-based entanglement infiltration technique, subnetworks may be configured within the network configuration mode. If there are multiple network configuration modes that can be used, the network configuration information may indicate one network configuration mode selected from among the currently operable network configuration modes. To this end, at least one network configuration mode may be defined, and detailed information about the at least one network configuration mode may be transmitted to the first terminal via a network configuration information (NCI) message. The network configuration modes may be generated based on an initial graph generated based on the connection status between nodes. The control node may obtain connection information with neighboring nodes from nodes included in the network to determine the initial graph.

[0256] In step S1905, the control node performs a route establishment procedure. The control node can determine a route associated with a transmission / reception flow between a transmitting node and a receiving node through the route establishment procedure. The route associated with the transmission / reception flow can be composed of nodes included in the network, links, or multi-hop segments generated through a LOCC procedure. Multi-hop segments can be used to form remote entanglements, and the control node can instruct nodes to perform measurements to determine whether a specific multi-hop segment can form a maximally entangled state.

[0257] The network configuration modes described above in FIGS. 18 and 19 may include at least one subnetwork. Furthermore, one network configuration mode may be configured with at least one subnetwork. In this case, the operation modes of nodes within the subnetwork may not be statically assigned, but may be designated as undefined. The undefined operation mode may be separately designated by the control node when the nodes perform the entanglement infiltration process.

[0258] A remote entangled state can be formed between a transmitting node and a receiving node through the procedures described above in FIGS. 18 and 19. Below, the path setting procedure performed to form the remote entangled state is described.

[0259] FIG. 20 illustrates an example of a procedure in which a first node performs route setting according to one embodiment of the present disclosure. FIG. 20 illustrates a method performed by a device included in a quantum network (e.g., a node of FIG. 13 , a node of FIG. 15 , a node of FIG. 16 , and a node A (1701), a node B (1702), and a node R (1703) of FIG. 17 ). In the description referring to FIG. 20 , an operating subject is referred to as a first node, and the first node is a device included in the quantum network, which may function as a transmitting node, a receiving node, or an intermediate node. In FIG. 20 , a control node is a device that controls nodes included in the quantum network, and may be a node included in the quantum network or an external device.

[0260] Referring to FIG. 20, in step S2001, the first node receives measurement-related information from the control node. The measurement-related information may include information regarding elements or segments that can be used to form remote entanglement between the transmitting node and the receiving node. For example, when a multi-hop segment is used to form remote entanglement, the measurement-related information may include information for establishing a multi-hop segment in which the first node is included. Specifically, the measurement-related information may include at least one of quantum channel information for performing the measurement, classical channel information for transmitting classical information, a subnetwork indicator, or information regarding the operation mode of the first node.

[0261] If the operation mode is set semi-statically, the operation mode of the first node can be indicated using a subnetwork indicator. Therefore, information regarding the operation mode can be omitted. However, if an entanglement infiltration method based on dynamic lattice transformation is used, the operation mode of the first node in the subnetwork of the network configuration mode can be set to an undetermined state. Therefore, a separate procedure for indicating the operation mode is required. Therefore, the information regarding the measurement can include information regarding the operation mode of the first node that is dynamically set for the subnetwork. Here, the information regarding the operation mode of the first node can include not only the information indicating the operation mode but also link pairing information. Here, the link pairing information can indicate a pair of quantum states on which a relay node should perform a measurement for entanglement, or can indicate two vertex nodes on which the relay node should relay.

[0262] In step S2003, the first node reports the measurement result to the control node. The measurement result may include information regarding whether the qubits held by the first node and the second node have been converted into a maximally entangled state. Here, the first node and the second node may be nodes that can be connected through other nodes. For example, if a 2-hop segment such as that shown in FIG. 17 is used in the configured subnetwork, the first node and the second node may convert the qubits they store into a maximally entangled state using a relay node. In this case, the first node may receive the Bell state measurement result from the relay node and perform a measurement procedure to convert the qubits stored by the first node and the qubits stored by the second node into a maximally entangled state through a measurement operator. The first node may report the measurement result, including whether the conversion result was successful, to the control node.

[0263] In step S2005, the first node receives information about a path determined based on the measurement results from the control node. Here, the path may be determined by the control node based on a multi-hop segment of a maximally entangled state that has been successfully converted to a maximally entangled state. Through the path, entanglement may be formed between a transmitting node and a receiving node using the multi-hop segment of the maximally entangled state. The information about the path may be transmitted to nodes included in the path and may include an entanglement distribution command about the path. The information about the path may indicate that the first node is included in the path where entanglement is formed between the transmitting node and the receiving node. The information about the path may be transmitted in a second entanglement distribution command message.

[0264] FIG. 21 illustrates an example of a procedure in which a control node performs route setting according to an embodiment of the present disclosure. FIG. 21 illustrates a method performed by a device controlling a quantum network. In the description referring to FIG. 21, an operating entity is referred to as a control node, and the control node may be one of the nodes constituting the quantum network (e.g., the node of FIG. 13, the node of FIG. 15, the node of FIG. 16, and the node A (1701), node B (1702), and node R (1703) of FIG. 17), or may refer to a separate control device that is distinct from the nodes of the quantum network. In FIG. 21, the control node may perform the role of a network core or a base station. In FIG. 21, it is assumed that the control node has determined a subnetwork on which data transmission will be performed.

[0265] Referring to FIG. 21, in step S2101, the control node transmits measurement information to the nodes. The measurement information may include information regarding elements or segments that can be used to form remote entanglement between the transmitting node and the receiving node. For example, when a multi-hop segment is used to form remote entanglement, the measurement information may include information for establishing the multi-hop segment. Specifically, the measurement information may include at least one of quantum channel information for performing the measurement, classical channel information for transmitting classical information, or information regarding the operating mode of each node. In this case, when using a dynamic lattice transformation-based entanglement infiltration method, the operating mode of nodes in a sub-network of the network configuration mode may be set to an undefined state. Therefore, to indicate the operating mode set to an undefined state, the measurement information may include information regarding an operating mode that is dynamically set for the sub-network. Therefore, the information regarding the operating mode of each node may include not only information indicating the operating mode but also link pairing information. Here, the link pairing information may indicate a pair of quantum states on which the relay node should perform a measurement for entanglement, or may indicate two vertex nodes on which the relay node should relay. Information regarding the measurement may be transmitted in the first entanglement distribution command message.

[0266] In step S2103, the control node receives measurement results from the nodes. The measurement results may include whether a multi-hop segment was successfully formed. For example, the measurement results may include information indicating whether the segment was successfully transformed into a maximally entangled state.

[0267] In step S2105, the control node determines path information based on the measurement results. Based on the received measurement results, the control node can determine which segments have been successfully converted to a maximally entangled state. Using the segments converted to a maximally entangled state, the control node can determine a path that can form remote entanglement between the transmitting node and the receiving node based on the received measurement results. Here, the path can be determined to include multi-hop segments that have been successfully converted to a maximally entangled state. Path information can be generated for each node belonging to the determined path and transmitted to the nodes included in the path. The path information can indicate that a first node is included in the path where entanglement is formed between the transmitting node and the receiving node. The path information can be transmitted in a second entanglement distribution command message.

[0268] In step S2107, the control node transmits path information to the nodes included in the path. Information about the determined path can only be transmitted to the nodes included in the path and can be transmitted via a classical channel. Nodes that receive the path information can perform a LOCC procedure with neighboring nodes. The transmitting node and receiving nodes can transmit or receive data through the determined path.

[0269] The path establishment procedure described above in FIGS. 20 and 21 may be performed to provide a path that can form entangled qubits between a transmitting node and a receiving node. The path establishment procedure may be triggered when a path for data transmission is required. For example, the control node may receive an entanglement distribution request message from a transmitting node requiring data transmission or a receiving node requiring data reception, and initiate a path establishment procedure for a subnetwork determined based on the entanglement distribution request message.

[0270] Referring to Figures 20 and 21, a route can be established based on a multi-hop segment. Below, the LOCC procedure for determining whether a multi-hop segment has been successfully formed is described.

[0271] FIG. 22 illustrates an example of a procedure for a first vertex node to report a measurement result according to one embodiment of the present disclosure. FIG. 22 illustrates a method performed by a device included in a quantum network (e.g., the node of FIG. 13, the node of FIG. 15, the node of FIG. 16, and the node A (1701) and node B (1702) of FIG. 17). In the description referring to FIG. 22, the operating subject is referred to as the first vertex node. For convenience of explanation, it is assumed that a 2-hop segment among the multi-hop segments is used. The nodes located at both ends of the 2-hop segment are referred to as the first vertex node and the second vertex node, and the node located in the middle of the two ends is referred to as a relay node. It is assumed that the first vertex node has received information regarding the measurement.

[0272] Referring to FIG. 22, in step S2201, the first vertex node shares entangled qubits with the relay node. To this end, the first vertex node can generate a pair of entangled qubits composed of a first qubit and a second qubit. One qubit of the pair of qubits can be stored in the first vertex node, and the other qubit can be transmitted to the relay node. In the same manner, the relay node can also share entangled qubits with the second vertex node.

[0273] In step S2203, the first vertex node receives a Bell state measurement result from the relay node. The Bell state measurement result may include information about the Bell state of the pair of qubits received by the relay node. The Bell state measurement result may be transmitted through a classical channel.

[0274] In step S2205, the first vertex node performs a measurement to transform into a maximally entangled state. The measurement to transform into a maximally entangled state can be performed using a measurement operator. The measurement operator can be determined based on the Schmidt coefficients of the pair of qubits that the first vertex node shares with the repeater node and the Schmidt coefficients of the pair of qubits that the second vertex node shares with the repeater node. The first vertex node measures the qubits that it stores based on the measurement operator.

[0275] In step S2207, the first vertex node reports a measurement result to the control node. The measurement result may include whether the states of the qubits between the first vertex node and the second vertex node have been successfully converted to a maximally entangled state. The measurement result may be transmitted via a classical channel.

[0276] FIG. 23 illustrates an example of a procedure for a relay node to perform a measurement according to an embodiment of the present disclosure. FIG. 23 illustrates a method performed by a device included in a quantum network (e.g., a node of FIG. 13 , a node of FIG. 15 , and a node R (1703) of FIG. 17 ). In the description referring to FIG. 23 , the operating entity is referred to as a relay node. When the LOCC procedure for lattice transformation is performed with a multi-hop segment consisting of two or more link hops as a basic unit, the relay node may be referred to as an intermediate node of the multi-hop segment. For the convenience of explanation, it is assumed below that a 2-hop segment is used among the multi-hop segments. The nodes located at both ends of the 2-hop segment are referred to as a first vertex node and a second vertex node, and the node located in the middle of both ends is referred to as a relay node. It is assumed that the relay node has received information regarding the measurement.

[0277] Referring to FIG. 23, in step S2301, the relay node shares qubits in an entangled state with the vertex nodes. The relay node can share one qubit in an entangled state with the first vertex node. That is, a first qubit and a second qubit in an entangled state can be generated, and the first qubit can be assigned to the first vertex node, and the second qubit can be assigned to the relay node. In a similar manner, a third qubit and a fourth qubit in an entangled state can be generated, and the third qubit can be assigned to the second vertex node, and the fourth qubit can be assigned to the relay node. At this time, the device that generates a pair of qubits can be the first vertex node or the second vertex node.

[0278] In step S2303, the relay node performs a Bell state measurement. The relay node measures the Bell state for a pair of qubits, consisting of the second qubit and the fourth qubit, that it stores. The measurement result can be expressed as one of four Bell states.

[0279] In step S2305, the relay node shares the Bell state measurement results with the first vertex node. The Bell state measurement results may include information about the Bell states of pairs of qubits stored by the relay node. The Bell state measurement results may be transmitted in the form of indices corresponding to each Bell state. The Bell state measurement results may be transmitted via a classical channel.

[0280] In FIGS. 22 and 23, the node generating the pair of entangled qubits is not limited to a specific node. While FIG. 22 illustrates nodes at both ends generating qubits, this is not limiting. For example, a relay node may generate a pair of entangled qubits and transmit one qubit from the pair of entangled qubits to other nodes.

[0281] Using the aforementioned procedure, a measurement procedure corresponding to the corresponding subnetwork can be performed, and a path between a transmitting node and a receiving node can be formed based on the measurement results. Here, the subnetwork refers to a subnetwork structure that can be defined within a network configuration mode. The network configuration mode and the subnetwork can be defined in various ways. The following describes a procedure in which at least one network configuration mode and subnetwork are determined, and the network configuration mode to be used for communication among the network configuration modes is transmitted.

[0282] FIG. 24 illustrates an example of a procedure by which a first node receives information regarding a network configuration mode according to an embodiment of the present disclosure. FIG. 24 illustrates a method performed by a device included in a quantum network (e.g., the node of FIG. 13 , the node of FIG. 15 , the node of FIG. 16 , and the node A (1701), node B (1702), and node R (1703) of FIG. 17 ). In the description referring to FIG. 24 , the operating entity is referred to as the first node. The first node of FIG. 24 may refer to one of the nodes included in the quantum network and may perform the function of a base station or a terminal.

[0283] In step S2401, the first node transmits connection information with a neighboring node to the control node. The connection information with the neighboring node may be transmitted in a network topology information (NTI) message. In order to obtain connection information with the neighboring node, the first node may establish a neighboring relationship with the neighboring nodes through a signal transmission and / or reception procedure. According to one embodiment, the first node may establish a neighboring relationship with its neighboring node through a hello message or the like, and generate an NTI message and transmit it to the control node. Here, the NTI message may include at least one of information on the neighboring node with which the first node has established a neighboring relationship, an initial link connectivity with the neighboring node, etc. Here, a neighbor is not necessarily a physical concept, but refers to a neighboring node with which a quantum entanglement link can be successfully formed.

[0284] In step S2403, the first node receives network configuration information (NCI). The network configuration information may include details regarding at least one network configuration mode determined by the control node. For example, the network configuration information may include at least one of an identifier for at least one network configuration mode, subnetwork configuration information for each of at least one network configuration mode, an operation mode (e.g., vertex / repeater / excluded) of the first node within each subnetwork, and neighboring node information of the first node within each subnetwork. For example, the network configuration information may include a network configuration mode having a structure as shown in FIG. 15b or 16b.

[0285] In step S2405, the first node monitors the link connectivity and reports it to the control node. The link connectivity can be determined through a measurement procedure between the first node and a neighboring node.

[0286] At step S2407, the first node receives information about a network configuration mode from the control node. The information about the network configuration mode may include information indicating the network configuration mode to be used for quantum communication. The first node can then be allocated communication resources and perform quantum communication based on the received information about the network configuration mode.

[0287] Information regarding the network configuration mode received by the first node may include information for indicating a network configuration mode determined by the control node among at least one network configuration mode included in the NCI message. The first node can determine which network configuration mode is applied based on the information for indicating the network configuration mode. Since the first node has obtained sub-network configuration information regarding the network configuration mode, the operation mode of the first node (vertex / repeater / excluded), and neighboring node information of the first node within each sub-network through the NCI message, the first node can perform quantum communication in the indicated network configuration mode.

[0288] FIG. 25 illustrates an example of a procedure in which a control node dynamically transmits information regarding a network configuration mode according to one embodiment of the present disclosure. FIG. 25 illustrates a method performed by a device controlling a quantum network. In the description referring to FIG. 25, an operating entity is referred to as a control node, and the control node may be one of the nodes constituting the quantum network (e.g., the node of FIG. 13, the node of FIG. 15, the node of FIG. 16, and the node A (1701), node B (1702), and node R (1703) of FIG. 17), or may refer to a separate control device that is distinct from the nodes of the quantum network.

[0289] In step S2501, the control node creates an initial network graph. The control node creates an initial network graph based on connection information between the nodes that make up the network and neighboring nodes. Here, the initial graph refers to a graph that represents the connection status of the nodes.

[0290] In step S2503, the control node transmits network configuration information. The network configuration information may include detailed information regarding at least one network configuration mode. The detailed information may include at least one of information regarding a sub-network of each network configuration mode, the role of the node in the sub-network, neighbor information, etc. To dynamically control the network configuration mode, at least one network configuration mode may be predefined by the control node. As an example, the network configuration information may include a network configuration mode having the structure of FIG. 15b or 16b.

[0291] In step S2505, the control node receives a link connectivity diagram. The link connectivity diagram can be measured by the node and reported to the control node via a classical channel. The reported link connectivity diagram can be used to determine a representative value of the entire link connectivity diagram. The representative value of the entire link connectivity diagram can be defined in various ways. For example, the representative value can be an average value or a minimum value of the entire link connectivity diagram.

[0292] In step S2507, the control node transmits information regarding the network configuration mode. The information regarding the network configuration mode may include information for indicating the network configuration mode to be used for quantum communication. To this end, the network configuration mode to be used for quantum communication may be determined by the control node as one of at least one network configuration mode defined in advance based on representative values ​​of link connectivity.

[0293] Information indicating the network configuration mode can be conveyed in various forms. For example, the information indicating the network configuration mode can be conveyed in the form of index values ​​using a table. In another example, the network configuration mode can be conveyed via a unique identifier or indicator.

[0294] In order to support entanglement distribution procedures for multiple transmitting and receiving pairs simultaneously, the network configuration mode can be designed so that the LOCC process to be performed by each node for the sub-networks can be performed simultaneously.

[0295] For example, if the overall network structure has a triangular lattice structure in which one node forms links with six neighboring nodes, as shown in FIGS. 15a and 16a, a network configuration mode can be set in which a sub-network of the triangular lattice structure and a sub-network of the Kagome lattice structure are defined, as shown in FIGS. 15a and 16a. For convenience of explanation, the sub-network of the triangular lattice structure will be referred to as the first sub-network, and the sub-network of the Kagome lattice structure will be referred to as the second sub-network.

[0296] First, the first sub-network of the triangular lattice structure is composed of a plurality of triangular units, and the triangular units can be configured in a form in which they are adjacent to each other and arranged continuously. Each triangular unit can have three sides and three vertices. At this time, the triangular unit can be composed of devices operating in three-vertex mode and three 2-hop segments connecting the devices operating in the three-vertex mode. Therefore, each side of the triangular unit can be composed of a 2-hop segment, and each vertex can be composed of a vertex node. Here, adjacent triangular units share one 2-hop segment, and the nodes at the vertices of each side can operate in the vertex mode of the 2-hop segment. Therefore, the first sub-network can form a triangular lattice form in which the triangular units are regularly arranged, as shown in the structure indicated by the thick solid lines in FIGS. 15A and 16A.

[0297] The second sub-network of the Kagome lattice structure can be composed of links formed by the dotted lines in Fig. 15a or links formed by the dotted lines in Fig. 16a. That is, the Kagome lattice structure of the second sub-network can be formed in a structure in which triangular units and hexagonal units with a single link hop as one side are repeatedly arranged. Here, a single link hop means a link that is directly connected without an intermediate node. Therefore, as shown in Fig. 11d, the triangular units of the Kagome lattice structure can be composed in a form in which they share vertices and the shape surrounding the hexagon is repeated. That is, the first sub-network can be determined in a form in which triangular units with a 2-hop segment as one side are repeated, and the second sub-network can be determined in a form in which triangular units and hexagonal units with a single link hop as one side are repeated.

[0298] To allow LOCC processes to be performed simultaneously, links are configured to be unshared between subnetworks. For example, as shown in FIGS. 15a and 16a, the first and second subnetworks can be configured to share no links with each other. That is, a single 2-hop segment is configured to be contained within only one subnetwork, and the subnetworks can be configured to spatially overlap within the overall network. Therefore, simultaneous transmission and reception flows can be supported in the first and second subnetworks.

[0299] Nodes within subnetworks can be configured as vertex nodes or relay nodes within each subnetwork. Here, devices operating in vertex mode within the first subnetwork can form links with other devices operating in vertex mode through two-hop segments, with six or fewer vertex nodes and two-hop segments. However, the vertex mode at the edge can be formed with six or fewer vertex nodes and two-hop segments.

[0300] In the first subnetwork, a fixed operating mode can be set for a specific node. Therefore, when it is decided to use the first subnetwork, the nodes can perform the fixed operating mode. On the other hand, in the second subnetwork, the operating mode can be set dynamically. The second subnetwork with a Kagome lattice structure can be converted into one of multiple rectangular lattice structures and used. Therefore, link pairing information for a specific node can be set differently for each of the multiple rectangular lattice structures. The rectangular lattice structures can be defined in various ways and are not limited to a specific method. For example, the Kagome lattice structure of the second subnetwork can be converted into a rectangular lattice structure formed by the dotted lines of FIG. 15b or FIG. 16b.

[0301] FIG. 26 illustrates an example flowchart of a lattice transformation-based entanglement infiltration procedure according to one embodiment of the present disclosure. In FIG. 26, it is assumed that at least one network configuration mode to which the dynamic lattice transformation-based entanglement infiltration technique can be applied is defined.

[0302] Referring to FIG. 26, in step S2601, a network configuration mode determination step is performed. The control node can determine at least one network configuration mode. Here, the network configuration mode can be defined so that a dynamic grid transformation-based entanglement infiltration procedure can be applied. The control node can transmit network configuration information including the determined at least one network configuration mode to nodes included in the network. The network configuration information can be transmitted in a format as shown in [Table 6] below.

[0303] NCI messageNet_config_idSubNet_id(for each Net_config_id)Percol_mode(for each SubNet_id)Neigh_id(for each SubNet_id)

[0304] In [Table 6], Net_config_id means an identifier for each network configuration mode, SubNet_id means an identifier of a subnetwork defined in each network configuration mode, Percol_mode means an identifier of an operation mode defined in each subnetwork, and Neigh_id means neighbor node information of each node in each subnetwork.

[0305] The control node can then determine an appropriate network configuration mode based on the link connectivity and network traffic characteristics of each link and transmit the determined network configuration mode identifier to the nodes. In the entanglement infiltration process based on dynamic lattice transformation, the operation mode may refer to the LOCC strategy that each node must perform to support an entanglement distribution request for any pair of transmitting and receiving nodes. These operation modes can be individually indicated through identifiers. The operation modes can be set to vertex mode, relay mode, non-inclusion mode, etc.

[0306] The operation mode can be assigned semi-statically or dynamically for each subnetwork. When the operation mode is assigned semi-statically, when a specific subnetwork is established, the LOCC procedure performed by each node in the subnetwork for the entanglement infiltration procedure can be fixed. Therefore, each node in the specific subnetwork can be configured to perform the same LOCC procedure for each entanglement distribution request. Therefore, the LOCC procedure to be performed by each node can be specified once only the subnetwork is determined. If the operation mode is assigned dynamically, the operation mode can be set to undefined. When the operation mode for a specific subnetwork is set to undefined in the network configuration information message, the operation mode in the corresponding subnetwork can be indicated by the first entanglement distribution command message described below. Therefore, the LOCC procedure performed by each node in the corresponding subnetwork can be dynamically assigned for each entanglement distribution request.

[0307] In step S2603, an entanglement distribution request step is performed. The entanglement distribution request step may be performed when information to be transmitted occurs between any two nodes included in the network. For example, when data to be transmitted to a transmitting node and a receiving node occurs, the transmitting node may transmit an entanglement distribution request message requesting entanglement distribution to the control node. The entanglement distribution request message may include information related to the transmitting node, the receiving node, information regarding QoS characteristics of the data (e.g., QCI, 5QI), and the amount of data. The control node may determine a subnetwork on which to perform an entanglement infiltration process to support the entanglement distribution request based on the information included in the entanglement distribution request message.

[0308] In step S2605, entanglement link generation and lattice transformation steps are performed. To generate an entanglement link, the control node may transmit a first entanglement distribution command to a plurality of nodes based on information included in an entanglement distribution request message. The first entanglement distribution command message may be transmitted to a plurality of nodes to be involved in an entanglement infiltration process. The first entanglement distribution command message may include a sub-network identifier that supports the entanglement distribution request, entanglement link pairing information for performing lattice transformation of a relay node, quantum channel resource information between neighboring nodes for each link included in the sub-network, and classical channel resource information. Here, the quantum channel resource information may include information about resources used for entanglement distribution between neighboring nodes for each link included in the sub-network. In addition, the classical channel resource information may be used in a LOCC procedure for lattice transformation or obtaining a maximally entangled state.

[0309] Link pairing information can only be transmitted to nodes operating in relay mode. Therefore, the operation mode of the node can be indirectly or implicitly indicated based on the presence or absence of link pairing information in the first entanglement distribution command message. If a subnetwork supporting dynamic lattice transformation is used, if the first entanglement distribution command message includes link pairing information, the node can confirm that its operation mode is relay mode. Conversely, if the first entanglement distribution command message does not include link pairing information, the node can confirm that its operation mode is vertex mode. In addition, the first entanglement distribution command message can separately include an entanglement operation mode (e.g., Percol_mode). Therefore, the operation mode for the node can be directly indicated as vertex mode or relay mode.

[0310] Nodes that receive the first entanglement distribution command message can perform the first entanglement distribution procedure based on the information included in the first entanglement distribution command message. Accordingly, each node can perform link entanglement formation and lattice transformation procedures. Each node can identify which subnetwork is being operated through the subnetwork identifier included in the first entanglement distribution command message. It can identify its own operating mode, which is dynamically determined in the corresponding subnetwork. As described above, the operating mode can be directly indicated or indirectly indicated based on the presence or absence of link pairing information. Each node can perform the LOCC operation that must be performed in the lattice transformation procedure based on the operating mode and link pairing information assigned to it. Through the LOCC operation, the process of forming link entanglement, performing lattice transformation, and obtaining maximally entangled link entanglement can be performed. Each node can report the result of link entanglement formation to the control node.

[0311] In this case, when the LOCC strategy is performed in which the lattice transformation process is performed with a 2-hop segment consisting of two link hops as the basic unit, the entanglement infiltration execution mode of each node in a specific subnetwork can be set to either vertex mode or relay mode based on the network configuration information message or the first entanglement infiltration command. Each node can perform the procedure described above in Fig. 17.

[0312] A control node that receives a report on the first entanglement distribution procedure can obtain information on successful segments. If there is at least one path between a transmitting node and a receiving node consisting of successful segments, step S2607 is performed. If there is no path between a transmitting node and a receiving node consisting of successful segments, the control node can declare the termination of entanglement distribution. At this time, the control node can transmit an entanglement distribution termination message to the nodes and instruct them to use a different subnetwork or a different network configuration mode.

[0313] In step S2607, entanglement exchange and end-to-end entanglement generation steps are performed. The second entanglement distribution command message may include classical channel resource information for transmitting the Bell state measurement results of the intermediate nodes to the transmitting node and the receiving node. Nodes operating in vertex mode perform a LOCC procedure for entanglement exchange based on the second entanglement distribution command message. As a result of successfully performing the entanglement exchange procedure, an entangled state may be generated between the transmitting node and the receiving node.

[0314] FIG. 27 illustrates an example of a procedure in which qUE performs lattice transformation-based entanglement penetration according to one embodiment of the present disclosure. FIG. 27 illustrates a method performed by a device included in a quantum network (e.g., a node of FIG. 13 , a node of FIG. 15 , a node of FIG. 16 , and nodes A (1701), B (1702), and R (1703) of FIG. 17 ). In the description referring to FIG. 27 , an operating entity is referred to as qUE, and qUE may be referred to as a network node, a node, a terminal, a quantum device, a quantum apparatus, a quantum terminal, a quantum node, and other terms having equivalent technical meanings thereto. At least some of the procedures of FIG. 27 may be integrated into one step or omitted. That is, the steps illustrated in FIG. 27 may be performed in various modified forms. In FIG. 27 , qUE is assumed to be controlled via qNB. In Figure 27, it is assumed that the qUE has received network configuration information from the qNB through an initial setup procedure.

[0315] Referring to FIG. 27, in step S2701, qUE receives a network configuration mode from qNB. The network configuration mode may be indicated by one of the network configuration mode identifiers included in the network configuration information message. qUE may obtain information about the subnetwork in which it is included in the corresponding network configuration mode by mapping the network configuration mode identifier received in the network configuration information message. In the network configuration mode, qUE may be included in multiple subnetworks, but the LOCC procedure that qUE must perform for each subnetwork may be fixedly defined or may not be defined for dynamic allocation. Here, the LOCC procedure may be indicated as an entanglement infiltration mode. For example, if a LOCC strategy is used in which a two-hop segment consisting of two link hops is performed as a basic unit in a specific subnetwork, the entanglement infiltration mode of qUE in the corresponding subnetwork may be assigned a fixed mode such as a vertex mode or a repeater mode, or may be assigned in an undefined state and then the entanglement infiltration mode may be assigned through a separate message. If the entanglement penetration execution mode for a specific subnetwork is set to undefined in the network configuration information message, the qUE can receive its own entanglement penetration execution mode through the first entanglement distribution command described below.

[0316] In step S2703, qUE receives a first entanglement distribution command and performs a first entanglement distribution procedure. The first entanglement distribution command may include a sub-network identifier. If the entanglement infiltration execution mode is fixedly assigned to each sub-network, qUE may identify a sub-network on which to perform the first entanglement distribution and may identify an entanglement infiltration execution mode corresponding to the sub-network. If the entanglement infiltration execution mode is set to an undefined state, the entanglement infiltration execution mode may be identified through the first entanglement distribution command. For example, if the first entanglement distribution command includes link pairing information, qUE may identify that its entanglement infiltration execution mode is a relay mode.

[0317] Furthermore, even if the entanglement infiltration execution mode is fixedly assigned, information included in the first entanglement distribution command may be preferentially applied. For example, even if the operation mode of a specific subnetwork is fixedly set to vertex mode or repeater mode within the network configuration information message, link pairing information or entanglement infiltration execution mode information may be included in the first entanglement distribution command. In this case, the qUE may determine its own operation mode by giving priority to the link pairing information or entanglement infiltration execution mode information included in the first entanglement distribution command.

[0318] The qUE can perform the first entanglement distribution procedure by performing the LOCC procedure corresponding to the confirmed entanglement infiltration execution mode. The first entanglement distribution command can include quantum channel resource information and classical channel resource information for performing the LOCC procedure. If the first entanglement distribution procedure for a 2-hop segment is performed, the procedures described above in FIG. 17 can be performed. If the entanglement infiltration procedure based on dynamic lattice transformation is performed, the qUE can check information about two neighboring vertex nodes included in the 2-hop segment based on the link pairing information included in the first entanglement distribution command message.

[0319] In step S2705, qUE transmits a first entanglement distribution report to qNB. The first entanglement distribution report may include whether the first entanglement distribution procedure performed in step S2703 was successful. The first entanglement distribution report may be performed by a node operating in vertex mode among the qUEs. qUE may transmit the first entanglement distribution report based on the classical channel resource information received in step S2703.

[0320] In step S2707, the qUE receives a second entanglement distribution command and performs a second entanglement distribution procedure. The qUE may receive the second entanglement distribution command from the qNB. The second entanglement distribution command may be transmitted to the qUEs operating as vertex nodes. The second entanglement distribution command may include information for performing an entanglement swapping procedure in the second entanglement distribution procedure. The information for performing the entanglement swapping procedure may include information for forming an end-to-end (E2E) entanglement based on segments among adjacent segments of the qUE in which the first entanglement distribution procedure has succeeded. For example, the information for performing the entanglement swapping procedure may include information on a pair of adjacent segments on which entanglement swapping is to be performed, and classical channel resource information to be used for transmitting a Bell state measurement result performed in the entanglement swapping procedure to a transmitting node and a receiving node. If qUE receives an entanglement distribution termination message rather than a second entanglement distribution command, qUE can terminate the entanglement distribution process without performing the second entanglement distribution step.

[0321] FIG. 28 illustrates an example of a procedure for a qNB to perform lattice transformation-based entanglement infiltration according to an embodiment of the present disclosure. FIG. 28 illustrates a method performed by a device controlling a quantum network. In the description referring to FIG. 28, an operating entity is referred to as a qNB, which may be referred to as a base station, a quantum base station, a control device, a central control device, a core network, a management node, a control node, a network node, and other terms having equivalent technical meanings thereto. The qNB of FIG. 28, the control node, may be one of the nodes constituting the quantum network (e.g., the node of FIG. 13, the node of FIG. 15, the node of FIG. 16, and the node A (1701), node B (1702), and node R (1703) of FIG. 17), or may refer to a separate control device that is distinct from the nodes of the quantum network. In FIG. 28, the control node may perform the role of a network core or a base station.

[0322] At least some of the procedures of FIG. 28 may be integrated into a single step or omitted. That is, the steps illustrated in FIG. 28 may be performed in various modified forms. In FIG. 28, it is assumed that qNB has transmitted network configuration information to qUE through an initial setup procedure. To this end, qNB may define at least one network configuration mode to which dynamic lattice transformation-based entanglement penetration is applicable through the initial setup procedure and include this in a network configuration information message and transmit it to qUE. In this case, the network configuration mode to which dynamic lattice transformation-based entanglement penetration is applicable means a mode in which the entanglement penetration operation mode is not fixedly set for each subnetwork, but is dynamically determined by qNB.

[0323] Referring to FIG. 28, in step S2801, the qNB transmits a network configuration mode. The network configuration mode may be indicated by one of the network configuration mode identifiers included in the network configuration information message. The network configuration mode may be transmitted to the qUE when the qNB decides to apply the entanglement infiltration technique based on lattice transformation. When a sub-network to which the dynamic lattice transformation-based entanglement infiltration is applicable is configured, the entanglement infiltration operation mode of the qUE in the corresponding sub-network may not be fixedly assigned and may be set to an undefined state. The LOCC procedure corresponding to each entanglement infiltration operation mode may be agreed upon in advance between the qNB and the qUE or indicated through a network configuration mode message, etc. Thereafter, the qNB may determine whether to apply the entanglement infiltration technique based on the link connectivity of the current network, traffic congestion, and QoS characteristics of the traffic. If the use of an entanglement infiltration technique based on dynamic lattice transformation is deemed appropriate, the qNB may indicate the application of the corresponding network configuration mode through a network configuration mode identifier that can apply dynamic lattice transformation-based techniques.

[0324] In step S2803, the qNB receives an entanglement distribution request. For the entanglement distribution request, a transmitting node or a receiving node may transmit an entanglement distribution request message to the qNB. The entanglement distribution request message may include information such as information about the transmitting node requesting the resource, information about the receiving node, information about QoS characteristics of the data (e.g., QCI, 5QI), and the amount of data. The qNB may determine a subnetwork on which to perform entanglement penetration for the entanglement distribution request by considering the information about the transmitting node, information about the receiving node, information about the QoS characteristics, and the network environment included in the entanglement distribution request message.

[0325] In step S2805, the qNB transmits a first entanglement distribution command and receives a first entanglement distribution result. The qNB may transmit the first entanglement distribution command to multiple qUEs included in the sub-network determined in step S2803. The first entanglement distribution command message may include at least one of quantum channel resource information, classical channel resource information, and a sub-network identifier to be used in performing the entanglement infiltration process.

[0326] In an entanglement infiltration method based on dynamic lattice transformation, the entanglement infiltration execution mode of a qUE included in a specific subnetwork may be set to an undefined state. Accordingly, the first entanglement distribution command message may include link pairing information. The operation mode may be acquired based on the link pairing information of the qUE. Here, the link pairing information refers to information regarding Bell state measurements performed by a relay node for lattice transformation. Accordingly, the link pairing information may indicate which qubits among a plurality of entangled state qubit pairs shared by the relay node with neighboring vertex nodes should perform Bell state measurements.

[0327] Since the link pairing information is only necessary for the qUE operating in the relay mode, the operation mode of the qUE can be indicated based on whether the link pairing information is included in the first entanglement distribution command message. That is, when the qNB sets the operation mode of the qUE to the relay mode, the qNB can transmit the first entanglement distribution command message including the first entanglement link pairing information. Conversely, when the qNB sets the operation mode of the qUE to the vertex mode, the qNB can transmit the first entanglement distribution command message that does not include the link pairing information.

[0328] Even if the entanglement infiltration mode for a subnetwork is fixedly set to a vertex mode or a repeater mode in the network configuration information message, the qNB may transmit a first entanglement distribution command message including link pairing information or entanglement infiltration mode information. In this case, the qUE may preferentially apply the entanglement infiltration mode acquired based on the first entanglement distribution command message. Accordingly, the qNB may temporarily and dynamically change the entanglement infiltration mode fixedly set for the subnetwork.

[0329] qNB receives the first entanglement distribution result from qUE. The first entanglement distribution result may include the result of the first entanglement distribution procedure performed by qUE. This allows qUE to communicate to qNB whether the first entanglement distribution procedure for each segment was successful or failed.

[0330] In step S2807, the qNB transmits a second entanglement distribution command and receives a second entanglement distribution result. The second entanglement distribution command may be transmitted if there is at least one end-to-end (E2E) path consisting of successful segments. The second entanglement distribution command message may include a LOCC procedure required for multi-hop entanglement exchange on the end-to-end path and classical channel resource information to be used for the LOCC procedure.

[0331] If there is no end-to-end (E2E) path that can be constructed with successful segments, the entanglement distribution procedures can be re-performed or the entanglement distribution procedure can be terminated. That is, the qNB can send a first entanglement distribution command message to perform the first entanglement distribution procedure or send an entanglement distribution termination message to terminate the entanglement distribution procedure.

[0332] FIG. 29 illustrates a first example of signaling for performing lattice transformation-based entanglement penetration according to one embodiment of the present disclosure. In FIG. 29 , signaling between a control node (2910) and nodes (2920) may be performed via a classical channel. The message conveyed in FIG. 29 is not limited to a specific format. For example, the message conveyed in FIG. 29 may be conveyed in the form of an RRC (radio resource control) message or a MAC CE.

[0333] Referring to FIG. 29, in step S2901, the control node (2910) receives an NTI message from nodes (2920). The NTI message may be generated by each node (2920) based on its neighboring node information during the network initialization step. The control node (2910) may determine the graph of the entire network based on the received NTI message.

[0334] In step S2903, the control node (2910) transmits an NCI message to nodes (2920). The NCI message may include information regarding at least one network configuration mode. The at least one network configuration mode may be determined based on the entire network graph determined in step S2901. Here, the at least one network configuration mode may include a network configuration mode to which an entanglement infiltration technique based on dynamic lattice transformation can be applied. When two sub-networks are defined in one network configuration mode, the NCI message may be transmitted in a format as shown in [Table 7] below.

[0335] NCI messageNet_config_idSubNet_id(for each Net_config_id)0 (triangular lattice)1 (Kagome lattice)Percol_mode(for each SubNet_id=0):0(vertex) or 1(repeater)Percol_mode(for each SubNet_id=1):2(undefined)Neigh_id(for each SubNet_id)

[0336] In [Table 7], a first sub-network of a triangular lattice structure and a second sub-network of a Kagome lattice structure can be defined within one network configuration mode. At this time, the index value of the first sub-network can be indicated as 0, and the index value of the second sub-network can be indicated as 1. In addition, an entanglement distribution procedure can be indicated to nodes (2920) that receive an NCI message for each of the sub-networks. At this time, the entanglement distribution procedure can be set through an indicator of an operation mode or an entanglement infiltration performance mode. The operation mode can be indicated as semi-static or dynamic. In the following, for convenience of explanation, it is assumed that the operation mode of the first sub-network is set to semi-static, and the operation mode of the second sub-network is set to dynamic. Therefore, as shown in [Table 7], with respect to the first sub-network, the operation mode of a node that receives an NCI message in which Percol_mode is indicated as 0 is set to vertex mode, and the node can perform a LOCC procedure for the vertex node. In addition, the operation mode of a node that has received an NCI message indicating Percol_mode as 1 for the first sub-network is set to a relay mode, and the node can perform a bell state measurement procedure for the relay node. In addition, nodes (2920) that have received an NCI message indicating Percol_mode as 2 for the second sub-network can confirm that the operation mode for the second sub-network is dynamically set.

[0337] Accordingly, each of the nodes (2920) can check information about at least one network configuration mode based on the NCI message received from the control node (2910). Each of the nodes (2920) can check sub-network information, an operation mode for the corresponding sub-network information, and neighboring node information for at least one network configuration mode. Since the operation mode for the first sub-network is determined, even if only the identifier of the first sub-network is transmitted to the nodes (2920), the nodes (2920) can check the LOCC procedure that they must perform. Since the operation mode for the second sub-network is undefined, the nodes (2920) can know that the operation mode for the second sub-network can be set through additional signaling.

[0338] In step S2905, the control node (2910) receives link connectivity information (LCI) reports from nodes (2920). The LCI reports may be delivered via messages specifically designed for LCI (e.g., the LCI_report message). The LCI_report message may include information regarding the link connectivity between itself and neighboring nodes. To this end, the nodes (2920) may monitor the link connectivity based on the NCI message.

[0339] Monitoring of link connectivity and transmission of LCI_report messages can be performed periodically or aperiodically. Information regarding the message transmission cycle can be transmitted as part of an NCI message or agreed upon between the control node (2910) and nodes (2920) via a separate signal. The control node (2910) can determine a representative value for the link connectivity of the network based on LCI_reports received from multiple nodes (2920).

[0340] In step S2907, the control node (2910) transmits information about a network configuration mode to the nodes (2920). The information about the network configuration mode may include a network configuration mode identifier, Net_config_id. The control node (2910) may select a network configuration mode suitable for the current network environment based on representative values ​​for link connectivity, the amount of current data traffic, or QoS characteristics of the data, and may transmit information about the selected network configuration mode. In this case, a network configuration mode to which a dynamic grid transformation-based entanglement penetration technique is applied may be selected.

[0341] Nodes (2920) can identify the network configuration mode corresponding to the Net_config_id through the received NCI message. Based on information about the identified network configuration mode, nodes (2920) can check information about the subnetwork to which they belong, their operation mode in the subnetwork, and information about neighboring nodes.

[0342] In step S2909, the control node (2910) receives an entanglement distribution request from nodes (2920). The entanglement distribution request may be transmitted via an ED_request message. When data terminating between a transmitting node and a receiving node occurs on the network, the transmitting node may transmit an ED_request message requesting entanglement resources to the control node (2910). The control node (2910) determines a subnetwork that will support the entanglement distribution request based on information about the transmitting node, receiving node, and QoS characteristics included in the ED_request message. The entanglement distribution request may be received from multiple nodes (2920). In this case, multi-flows may be supported based on an entanglement infiltration technique based on a semi-static or dynamic lattice transformation.

[0343] In step S2911, the control node (2910) transmits a first entanglement distribution command to the nodes (2920). The first entanglement distribution command message may be transmitted via an ED_ph1_cmd message. The first entanglement distribution command message may include at least one of a qCH, a cCH, a SubNet_id value, and link pairing information (e.g., link_pair), and the first entanglement distribution command message may be transmitted in a format as shown in [Table 8] below.

[0344] 1st entanglement distribution commandqCH: quantum channel resources for entanglement distribution at each linkcCH: classical channel resources for LOCC at each two-hop segmentSubNet_id: sub-network index where entanglement percolation is performedLink_pair(only for repeater nodes):Link pairing information to perform ZZ bell measurement for lattice transformation

[0345] In [Table 8], qCH indicates quantum channel resources for entanglement distribution, cCH indicates classical channel resources for LOCC procedure, SubNet_id indicates a subnetwork, and Link_pair may indicate link pairing information for nodes (2920) operating in relay mode to perform Bell state measurement. At this time, the link pairing information may be included only in the first entanglement distribution message transmitted to nodes (2920) operating in relay mode. Nodes (2920) may identify a subnetwork on which entanglement distribution procedure is to be performed based on SubNet_id. In addition, nodes (2920) may recognize their own operation mode (e.g., Percol_mode) and LOCC procedure defined therefor in the corresponding subnetwork based on the subnetwork indicator (e.g., SubNet_id) and link pairing information (e.g., Link_pair).

[0346] In step S2913, nodes (2920) perform a first entanglement distribution procedure. The first entanglement distribution procedure may include a procedure for forming a multi-hop segment that can be used in a sub-network. To form the multi-hop segment, nodes (2920) may perform a LOCC procedure or a measurement procedure based on the operation mode corresponding to the determined sub-network. The first entanglement distribution procedure may be performed based on the qCH and cCH acquired in step S2911.

[0347] In step S2915, the control node (2910) receives a first entanglement distribution report from the nodes (2920). The first entanglement distribution report may include whether the first entanglement distribution procedure was successfully performed by the nodes (2920). If the control node (2910) receives the first entanglement distribution report indicating the success of the first distribution procedure, it may be determined that a multi-hop segment including the corresponding node has been successfully formed.

[0348] In step S2917, the control node (2910) transmits a second entanglement distribution command. The control node (2910) can determine whether end-to-end entanglement can be formed for the transmitting node and receiving node that requested entanglement distribution based on the received successful segments. If there is at least one path that can form end-to-end entanglement by combining the successful segments, the control node (2910) can transmit a second entanglement distribution command to the nodes (2920) on the path. The second entanglement distribution command can be transmitted via the ED_ph2_cmd message.

[0349] In step S2919, nodes (2920) perform a second entanglement distribution procedure. Nodes (2920) that receive the second entanglement distribution command can recognize that they are included in the transmission and reception path. Nodes (2920) can set their operation mode in a specific sub-network to be semi-static or dynamic. Nodes (2920) can perform a LOCC procedure corresponding to the specific sub-network. Nodes (2920) can perform an entanglement exchange procedure based on the information included in the second entanglement distribution command.

[0350] FIG. 30 illustrates a second example of signaling for performing lattice transformation-based entanglement penetration according to one embodiment of the present disclosure. In FIG. 30 , signaling between a control node (3010) and nodes (3020, 3030, and 3040) may be performed via a classical channel. The message conveyed in FIG. 30 is not limited to a specific form. For example, the message conveyed in FIG. 30 may be conveyed in the form of an RRC (radio resource control) message or a MAC CE.

[0351] Referring to FIG. 30, in step S3001, the control node (3010) and nodes (3020, 3030, 3040) included in the network perform an initial connection procedure. Through the initial connection procedure, resources regarding classical channels related to nodes (3020, 3030, 3040) included in the network can be established. In subsequent procedures, nodes (3020, 3030, 3040) included in the network can transmit or receive classical information through the established classical channels.

[0352] In step S3003, the control node (3010) and nodes (3020, 3030, 3040) included in the network perform a network configuration procedure. Through the network configuration procedure, at least one network configuration mode can be set for the nodes (3020, 3030, 3040) included in the network. The control node (3010) can determine at least one network configuration mode and transmit information about the corresponding network configuration mode to the nodes (3020, 3030, 3040). The network configuration mode can include at least one sub-network and can be defined so that a semi-static or static lattice transformation-based entanglement infiltration procedure can be applied. In the following, for the convenience of explanation, it is assumed that multiple network configuration modes are defined and a first network configuration mode to which a semi-static or static lattice transformation-based entanglement infiltration procedure can be applied is used. At this time, it is assumed that the first network configuration mode is composed of a first sub-network and a second sub-network, and that the first sub-network has a semi-statically set operation mode, and the second sub-network has a dynamically set operation mode.

[0353] In step S3005, the transmitting node (3020) transmits an entanglement distribution request message to the control node (3010). The entanglement distribution request message may be transmitted based on the triggering of a specific event. For example, when the transmitting node (3020) has data to transmit or detects an event that results in a lack of communication resources, the transmitting node (3020) may generate and transmit an entanglement distribution request message.

[0354] In step S3007, the control node (3010) transmits a first entanglement distribution command to the transmitting node (3020), the receiving node (3030), and the intermediate nodes (3040). The first entanglement distribution command may be transmitted via a message (e.g., an ED_ph1_cmd message) specifically designed to transmit information related to the first entanglement distribution command. The first entanglement distribution command message may include at least one of a qCH, a cCH, a SubNet_id value, or a Link_pair. Here, qCH may indicate a quantum channel resource, and cCH may indicate a classical channel resource. In this case, cCH may be transmitted as an index value indicating one of the classical channels set in the initial access procedure. In addition, qCH may indicate a quantum channel resource required for the entanglement infiltration process. SubNet_id means a subnetwork identifier set in the first network configuration mode, and may be indicated by an index value. For convenience of explanation, it is assumed that SubNet_id is passed as a value indicating a second subnetwork to which dynamic lattice transformation can be applied. Link_pair can indicate link pairing information and can only be passed to nodes operating in relay mode. Link pairing information can indicate a pair of quantum states on which a relay node should perform measurements for entanglement, or two vertex nodes that the relay node should relay.

[0355] In step S3009, the transmitting node (3020), the receiving node (3030), and the intermediate nodes (3040) perform a first entanglement distribution procedure. Through the first entanglement distribution procedure, each node (3020, 3030, 3040) can form a multi-hop segment with other nodes. For example, when a 2-hop segment is used in the sub-network, at least one of the procedures described in FIGS. 22 and 23 can be performed, and as a result, the qubits between the vertex nodes of the 2-hop segment can be transformed into a maximally entangled state. At this time, in the second sub-network to which the dynamic lattice transformation is applied, each node (3020, 3030, 3040) can identify the operation mode to be performed based on the Link_pair received in step S3007. A node that receives the Link_pair in the second sub-network can recognize that it is in relay mode and can perform a bell state measurement based on the link pairing information.

[0356] In step S3011, the transmitting node (3020), the receiving node (3030), and the intermediate nodes (3040) transmit a first entanglement distribution report to the control node (3010). The first entanglement distribution report may be transmitted by a node operating in vertex mode. The first entanglement distribution report may include whether the transformation to a maximally entangled state for each segment was successful.

[0357] In step S3013, the control node (3010) transmits a second entanglement distribution command to the transmitting node (3020), the receiving node (3030), and the intermediate nodes (3040). The second entanglement distribution command may be transmitted if there exists a path between at least one transmitting node (3020) and the receiving node (3030) that consists of segments that have been successfully converted to a maximally entangled state. The second entanglement distribution command message may include a LOCC procedure required for multi-hop entanglement exchange on the end-to-end path and classical channel resource information cCH to be used in the LOCC procedure.

[0358] In step S3015, the transmitting node (3020), the receiving node (3030), and the intermediate nodes (3040) perform a second entanglement distribution procedure. The transmitting node (3020), the receiving node (3030), and the intermediate nodes (3040) may perform a LOCC procedure for the second entanglement distribution procedure.

[0359] In step S3017, the transmitting node (3020) and the receiving node (3030) perform data communication using the entangled state. The transmitting node (3020) can transmit data using remote entangled qubits. The method by which the data is transmitted is not limited to any particular method.

[0360] Although the information regarding classical channels for the LOCC procedure is described in FIGS. 29 and 30 as being included in the first entanglement distribution command and the second entanglement distribution command, the present invention is not limited thereto. Resources regarding classical channels can be configured in the form of resource sets. Through an initial configuration procedure, classical channels used for a specific subnetwork can be semi-statically allocated, and the relationship between the subnetwork and the classical channel can be defined. In this case, even if only the identifier for the subnetwork is transmitted to the nodes, the nodes can check the classical channel information corresponding to the subnetwork. Quantum channel information can also be checked in the same way as classical channel information. Therefore, when the quantum channel resources and classical channel resources used for a specific subnetwork are semi-statically configured, the qCH and cCH can be indirectly or implicitly indicated. Therefore, direct transmission of the qCH and cCH can be omitted.

[0361] In the present disclosure, an entanglement distribution request may be used to request remote entanglement generation for data communication, and is not limited to a specific name. Accordingly, an entanglement distribution request may be referred to as an entanglement generation request, a scheduling request, a channel setup request, a resource allocation request, a resource setup request, a quantum channel setup request, a quantum channel configuration request, or other technically equivalent names.

[0362] Fig. 31 illustrates the comparison results of the entanglement penetration performance of the proposed technique according to one embodiment of the present disclosure and the Kagome lattice structure. In Fig. 31, the method utilizing the square lattice-based sub-network structure proposed in the present disclosure is denoted as Square, and the Kagome lattice-based sub-network structure is denoted as Kagome. Referring to Fig. 31, it can be seen that the technique utilizing the square lattice-based sub-network structure has a higher penetration probability than the technique utilizing the Kagome lattice-based sub-network structure. This means that the technique utilizing the square lattice-based sub-network structure has a lower penetration threshold. Therefore, when utilizing the square lattice-based sub-network structure proposed in the present disclosure, the entanglement penetration technique can be applied to a wider operating range.

[0363] Fig. 32 illustrates the results of comparing the network resource efficiency of the proposed technique according to one embodiment of the present disclosure and the Kagome lattice structure. In Fig. 32, the method of utilizing the square lattice-based sub-network structure proposed in the present disclosure is indicated as Square, and the Kagome lattice-based sub-network structure is indicated as Kagome. Referring to Fig. 32, it can be seen that the technique utilizing the square lattice-based sub-network structure can achieve higher network resource efficiency than the technique utilizing the Kagome lattice-based sub-network configuration method. The network resource efficiency of Fig. 32 is determined by the entanglement penetration rate. Network resource usage The value obtained by dividing by ( ) means. The Kagome lattice-based subnetwork structure uses the entire link resources of the network (i.e., ), the square lattice-based network structure in this disclosure can achieve a higher entanglement penetration rate even though it utilizes only 66.67% of the total network resources. Since the proposed square lattice-based network structure can achieve a higher entanglement penetration rate, higher network resource efficiency can be achieved compared to the Kagome lattice network structure.

[0364] The following effects can be achieved through the semi-static grid transformation-based sub-network configuration method proposed in this disclosure.

[0365] - Support of multiple QoS characteristics: In an environment where data with different QoS classes are mixed, the entanglement distribution procedure can be efficiently supported for transmission and reception flows with heterogeneous QoS characteristics.

[0366] - Operating range expansion of entanglement percolation: The entanglement percolation method based on dynamic lattice transformation proposed in this disclosure can utilize a square lattice-based subnetwork with a lower percolation threshold compared to a technique utilizing a Kagome lattice-based subnetwork structure. Therefore, the entanglement percolation technique can be applied to a wider operating range.

[0367] - Network efficiency enhancement: The entanglement penetration method based on dynamic lattice transformation proposed in this specification can utilize only link resources corresponding to 66.67 of the subnetworks of the Kagome lattice structure. Therefore, by transforming the subnetworks of the Kagome lattice structure into subnetworks of the square lattice structure, network resource usage can be reduced and a higher entanglement penetration rate can be achieved.

[0368] Below, examples of wireless device utilization to which various embodiments of the present disclosure are applied are described.

[0369] Figure 33 illustrates an example of a wireless device applicable to the present disclosure. The wireless device may be implemented in various forms depending on the use case / service (see Figure 1).

[0370] Referring to FIG. 33, the wireless device (200) corresponds to the wireless device (200) of FIG. 2 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (200) may include a communication unit (210), a control unit (220), a memory unit (230), and additional elements (240). The communication unit may include a communication circuit (212) and a transceiver(s) (214). For example, the communication circuit (212) may include one or more processors (202) and / or one or more memories (204) of FIG. 2. For example, the transceiver(s) (214) may include one or more transceivers (206) and / or one or more antennas (208) of FIG. 2. The control unit (220) is electrically connected to the communication unit (210), the memory unit (230), and the additional elements (240) and controls the overall operations of the wireless device. For example, the control unit (220) can control the electrical / mechanical operations of the wireless device based on the program / code / command / information stored in the memory unit (230). In addition, the control unit (220) can transmit information stored in the memory unit (230) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (210), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (230).

[0371] The additional element (240) may be configured in various ways depending on the type of the wireless device. For example, the additional element (240) may include at least one of a power unit / battery, an input / output unit (I / O unit), a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 1, 100a), a vehicle (Fig. 1, 100b-1, 100b-2), an XR device (Fig. 1, 100c), a portable device (Fig. 1, 100d), a home appliance (Fig. 1, 100e), an IoT device (Fig. 1, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 1, 400), a base station (Fig. 1, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0372] In FIG. 33, various elements, components, units / parts, and / or modules within the wireless device (200) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (210). For example, within the wireless device (200), the control unit (220) and the communication unit (210) may be wired, and the control unit (220) and a first unit (e.g., 230, 240) may be wirelessly connected via the communication unit (210). In addition, each element, component, unit / part, and / or module within the wireless device (200) may further include one or more elements. For example, the control unit (220) may be composed of a set of one or more processors. For example, the control unit (220) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of RAM (Random Access Memory), DRAM (Dynamic RAM), ROM (Read Only Memory), flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0373] Below, the implementation example of Fig. 33 is described in more detail with reference to the drawings.

[0374] Figure 34 illustrates examples of portable devices applicable to the present disclosure. Portable devices may include smartphones, smart pads, wearable devices (e.g., smartwatches, smartglasses), and portable computers (e.g., laptops). Portable devices may also be referred to as mobile stations (MS), user terminals (UT), mobile subscriber stations (MSS), subscriber stations (SS), advanced mobile stations (AMS), or wireless terminals (WT).

[0375] Referring to FIG. 34, the portable device (200) may include an antenna unit (208), a communication unit (210), a control unit (220), a memory unit (230), a power supply unit (240a), an interface unit (240b), and an input / output unit (240c). The antenna unit (208) may be configured as a part of the communication unit (210). Blocks 210 to 230 / 240a to 240c of FIG. 34 correspond to blocks 210 to 230 / 240 of FIG. 33, respectively.

[0376] The communication unit (210) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (220) can control components of the mobile device (200) to perform various operations. The control unit (220) can include an AP (Application Processor). The memory unit (230) can store data / parameters / programs / codes / commands required for operating the mobile device (200). In addition, the memory unit (230) can store input / output data / information, etc. The power supply unit (240a) supplies power to the mobile device (200) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (240b) can support connection between the mobile device (200) and other external devices. The interface unit (240b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (240c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (240c) may include a camera, a microphone, a user input unit, a display unit (240d), a speaker, and / or a haptic module.

[0377] For example, in the case of data communication, the input / output unit (240c) obtains information / signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information / signals can be stored in the memory unit (230). The communication unit (210) converts the information / signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. In addition, the communication unit (210) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information / signals. The restored information / signals can be stored in the memory unit (230) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (240c).

[0378] Figure 35 illustrates examples of vehicles or autonomous vehicles applicable to the present disclosure. The vehicles or autonomous vehicles may be implemented as mobile robots, cars, trains, manned / unmanned aerial vehicles (AVs), ships, etc.

[0379] Referring to FIG. 35, a vehicle or autonomous vehicle (200-1) may include an antenna unit (208-1), a communication unit (210-1), a control unit (220-1), a driving unit (240a-1), a power supply unit (240b-1), a sensor unit (240c-1), and an autonomous driving unit (240d-1). The antenna unit (208-1) may be configured as a part of the communication unit (210-1). Blocks 210-1 / 230-1 / 240a-1 to 240d-1 of FIG. 35 correspond to blocks 210 / 230 / 240 of FIG. 33, respectively.

[0380] The communication unit (210-1) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, roadside base stations (ROS), etc.), and servers. The control unit (220-1) can control elements of the vehicle or autonomous vehicle (200-1) to perform various operations. The control unit (220-1) may include an ECU (Electronic Control Unit). The drive unit (240a-1) can drive the vehicle or autonomous vehicle (200-1) on the ground. The drive unit (240a-1) may include an engine, a motor, a power train, wheels, brakes, a steering device, etc. The power supply unit (240b-1) supplies power to the vehicle or autonomous vehicle (200-1) and may include a wired / wireless charging circuit, a battery, etc. The sensor unit (240c-1) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (240c-1) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (240d-1) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.

[0381] For example, the communication unit (210-1) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (240d-1) can generate an autonomous driving route and driving plan based on the acquired data. The control unit (220-1) can control the drive unit (240a-1) so that the vehicle or autonomous vehicle (200-1) moves along the autonomous driving route according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (210-1) can irregularly / periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit (240c-1) can acquire vehicle status and surrounding environment information. The autonomous driving unit (240d-1) can update the autonomous driving route and driving plan based on newly acquired data / information. The communication unit (210-1) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to an external server. The external server can predict traffic information data in advance using AI technology, etc. based on information collected from the vehicle or autonomous vehicles, and provide the predicted traffic information data to the vehicle or autonomous vehicles. If the device (220-2) is an autonomous vehicle, it can perform the same procedure as the vehicle or autonomous vehicle (200-1). In addition, if the device (220-2) is a base station or a roadside base station, the device (220-2) can transmit data, control signals, etc. to the vehicle or autonomous vehicle (200-1) through the communication unit (210-2).

[0382] Figure 36 illustrates an example of a vehicle applicable to the present disclosure. The vehicle may also be implemented as a means of transportation, a train, an aircraft, a ship, etc. Referring to Figure 36, the vehicle (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), and a position measurement unit (240b). Here, blocks 210 to 230 / 240a to 240b correspond to blocks 210 to 230 / 240 of Figure 33, respectively.

[0383] The communication unit (210) can transmit and receive signals (e.g., data, control signals, etc.) with other vehicles or external devices such as base stations. The control unit (220) can control components of the vehicle (200) to perform various operations. The memory unit (230) can store data / parameters / programs / codes / commands that support various functions of the vehicle (100). The input / output unit (240a) can output AR / VR objects based on information in the memory unit (230). The input / output unit (240a) can include a HUD. The position measurement unit (240b) can obtain position information of the vehicle (200). The position information can include absolute position information of the vehicle (200), position information within a driving line, acceleration information, position information with respect to surrounding vehicles, etc. The position measurement unit (240b) can include GPS and various sensors.

[0384] For example, the communication unit (210) of the vehicle (200) can receive map information, traffic information, etc. from an external server and store them in the memory unit (230). The location measurement unit (240b) can obtain vehicle location information through GPS and various sensors and store the information in the memory unit (230). The control unit (220) can create a virtual object based on the map information, traffic information, and vehicle location information, and the input / output unit (240a) can display the created virtual object on the vehicle window (240a-1, 240a-2). In addition, the control unit (220) can determine whether the vehicle (200) is being driven normally within the driving line based on the vehicle location information. If the vehicle (200) abnormally deviates from the driving line, the control unit (220) can display a warning on the vehicle window through the input / output unit (240a). Additionally, the control unit (220) can broadcast a warning message regarding driving abnormalities to surrounding vehicles through the communication unit (210). Depending on the situation, the control unit (220) can transmit vehicle location information and information regarding driving / vehicle abnormalities to relevant authorities through the communication unit (210).

[0385] Figure 37 illustrates examples of XR devices applicable to the present disclosure. The XR devices may be implemented as HMDs, head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, and the like.

[0386] Referring to FIG. 37, the XR device (200a) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), a sensor unit (240b), and a power supply unit (240c). Here, blocks 210 to 230 / 240a to 240c of FIG. 37 correspond to blocks 210 to 230 / 240 of FIG. 33, respectively.

[0387] The communication unit (210) can transmit and receive signals (e.g., media data, control signals, etc.) with external devices such as other wireless devices, portable devices, or media servers. The media data can include videos, images, sounds, etc. The control unit (220) can control components of the XR device (200a) to perform various operations. For example, the control unit (220) can be configured to control and / or perform procedures such as video / image acquisition, (video / image) encoding, metadata generation and processing, etc. The memory unit (230) can store data / parameters / programs / codes / commands required for driving the XR device (200a) / generating XR objects. The input / output unit (240a) can obtain control information, data, etc. from the outside, and output the generated XR object. The input / output unit (240a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and / or a haptic module. The sensor unit (240b) can obtain the XR device status, surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar. The power supply unit (240c) supplies power to the XR device (200a) and may include a wired / wireless charging circuit, a battery, etc.

[0388] For example, the memory unit (230) of the XR device (200a) may include information (e.g., data, etc.) required for creating an XR object (e.g., AR / VR / MR object). The input / output unit (240a) may obtain a command to operate the XR device (200a) from the user, and the control unit (220) may operate the XR device (200a) according to the user's operating command. For example, when a user attempts to watch a movie, news, etc. through the XR device (200a), the control unit (220) may transmit content request information to another device (e.g., a mobile device (200b)) or a media server through the communication unit (230). The communication unit (230) may download / stream content such as movies and news from another device (e.g., a mobile device (200b)) or a media server to the memory unit (230). The control unit (220) controls and / or performs procedures such as video / image acquisition, (video / image) encoding, and metadata generation / processing for content, and can generate / output an XR object based on information about surrounding space or real objects acquired through the input / output unit (240a) / sensor unit (240b).

[0389] In addition, the XR device (200a) is wirelessly connected to the mobile device (200b) through the communication unit (210), and the operation of the XR device (200a) can be controlled by the mobile device (200b). For example, the mobile device (200b) can act as a controller for the XR device (200a). To this end, the XR device (200a) can obtain 3D location information of the mobile device (200b), and then generate and output an XR object corresponding to the mobile device (200b).

[0390] Figure 38 illustrates examples of robots applicable to the present disclosure. Robots can be classified into industrial, medical, household, and military types, depending on their intended use or field.

[0391] Referring to FIG. 38, the robot (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), a sensor unit (240b), and a driving unit (240c). Here, blocks 210 to 230 / 240a to 240c of FIG. 38 correspond to blocks 210 to 230 / 240 of FIG. 33, respectively.

[0392] The communication unit (210) can transmit and receive signals (e.g., driving information, control signals, etc.) with external devices such as other wireless devices, other robots, or control servers. The control unit (220) can control components of the robot (200) to perform various operations. The memory unit (230) can store data / parameters / programs / codes / commands that support various functions of the robot (200). The input / output unit (240a) can obtain information from the outside of the robot (200) and output information to the outside of the robot (200). The input / output unit (240a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and / or a haptic module. The sensor unit (240b) can obtain internal information of the robot (200), surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, a radar, etc. The driving unit (240c) may perform various physical operations, such as moving the robot joints. In addition, the driving unit (240c) may enable the robot (200) to drive on the ground or fly in the air. The driving unit (240c) may include an actuator, a motor, wheels, brakes, propellers, etc.

[0393] Figure 39 illustrates an example of an AI device applicable to the present disclosure.

[0394] AI devices can be implemented as fixed or mobile devices, such as TVs, projectors, smartphones, PCs, laptops, digital broadcasting terminals, tablet PCs, wearable devices, set-top boxes (STBs), radios, washing machines, refrigerators, digital signage, robots, and vehicles.

[0395] Referring to FIG. 39, the AI ​​device (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a / 240b), a learning processor unit (240c), and a sensor unit (240d). Blocks 210 to 230 / 240a to 240d of FIG. 39 correspond to blocks 210 to 230 / 140 of FIG. 33, respectively.

[0396] The communication unit (210) can transmit and receive wired and wireless signals (e.g., sensor information, user input, learning models, control signals, etc.) with external devices such as other AI devices (e.g., 100a to 100f, 120 of FIG. 1) or AI servers (e.g., 100g of FIG. 1) using wired and wireless communication technology. To this end, the communication unit (210) can transmit information within the memory unit (230) to the external device or transfer a signal received from the external device to the memory unit (230).

[0397] The control unit (220) may determine at least one executable operation of the AI ​​device (200) based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the control unit (220) may control components of the AI ​​device (200) to perform the determined operation. For example, the control unit (220) may request, search, receive, or utilize data from the learning processor unit (240c) or the memory unit (230), and may control components of the AI ​​device (200) to perform at least one executable operation, a predicted operation, or an operation determined to be desirable. In addition, the control unit (220) may collect history information including the operation contents of the AI ​​device (200) or user feedback on the operation, and store the collected history information in the memory unit (230) or the learning processor unit (240c), or transmit the collected history information to an external device such as an AI server (FIG. 1, 100g). The collected history information may be used to update a learning model.

[0398] The memory unit (230) can store data that supports various functions of the AI ​​device (200). For example, the memory unit (230) can store data obtained from the input unit (240a), data obtained from the communication unit (210), output data of the learning processor unit (240c), and data obtained from the sensing unit (140). In addition, the memory unit (230) can store control information and / or software codes necessary for the operation / execution of the control unit (220).

[0399] The input unit (240a) can obtain various types of data from the outside of the AI ​​device (200). For example, the input unit (220) can obtain learning data for model learning, input data to which the learning model will be applied, etc. The input unit (240a) may include a camera, a microphone, and / or a user input unit. The output unit (240b) may generate output related to vision, hearing, or touch. The output unit (240b) may include a display unit, a speaker, and / or a haptic module, etc. The sensing unit (140d) can obtain at least one of internal information of the AI ​​device (200), information about the surrounding environment of the AI ​​device (200), and user information using various sensors. The sensing unit (140d) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar, etc.

[0400] The learning processor unit (240c) can train a model composed of an artificial neural network using learning data. The learning processor unit (240c) can perform AI processing together with the learning processor unit of the AI ​​server (Fig. 1, 100g). The learning processor unit (240c) can process information received from an external device via the communication unit (210) and / or information stored in the memory unit (230). In addition, the output value of the learning processor unit (240c) can be transmitted to an external device via the communication unit (210) and / or stored in the memory unit (230).

[0401] FIG. 40 illustrates an example of a quantum communication device applicable to the present disclosure. Referring to FIG. 40, the quantum communication device (250) may include a quantum operator (252), a quantum measuring device (254), a quantum memory (253), an entanglement generator (255), and an optical signal converter (256). Although not illustrated in FIG. 40, the quantum communication device (250) may include a central processing unit or control unit for controlling the information source (251), the quantum operator (252), the quantum measuring device (254), the quantum memory (253), the entanglement generator (255), and the optical signal converter (256).

[0402] An information source (251) can generate quantum information in a quantum communication system. Here, the quantum information can be generated based on classical information. Quantum information can be referred to as quantum bits, qubits, and equivalent technical names. For convenience of explanation, it is assumed below that quantum information is generated as qubits having a specific quantum state. Classical information can be information in which a data stream is encoded, and when classical information is converted into qubits, a quantum encoding procedure can be performed. The information source (251) can transfer the generated qubits to a quantum memory (253). Here, the qubits can perform an operation through a quantum operator (252) and then transfer the operation to the quantum memory (253).

[0403] Additionally, the information source (251) can convert qubits into classical information. Therefore, the information source (251) can decode qubits received from the quantum memory (253) and convert them into classical information. When qubits are converted into classical information, a quantum decoding procedure can be performed.

[0404] A quantum operator (252) can convert a state of a qubit into another state. The quantum operator (252) can include a quantum gate. The quantum gate can be configured in various ways and can be implemented as at least one single gate, at least one multiple gate, or a combination thereof. Here, the single gate can mean a Hadamard gate, a Pauli-X gate, a Pauli-Y gate, or a Pauli-Z gate, and the multiple gates can mean a CNOT (controlled-not gate). The quantum operator (252) can receive a qubit from an information source (251) or a quantum memory (253), perform a quantum operation, and then transfer the qubit on which the operation was performed to the information source (251) or the quantum memory (253).

[0405] A quantum measuring device (254) can measure the state of a qubit. The quantum measuring device (254) can receive a qubit from a quantum memory (253) and measure the state of the received qubit. As a result of performing the measurement, the quantum state of the qubit can be collapsed. The collapsed qubit state can be converted into classical data. The measured qubit state can be transmitted to a central processing unit or a control unit.

[0406] A quantum memory (253) can store qubits for a certain period of time or permanently. The quantum memory (253) can be implemented so that changes in the state of the qubit can be minimized in order to reduce loss of the qubit. The quantum memory (253) can be implemented in various forms and is not limited to a specific form. For example, if the qubit is implemented using a photon, the quantum memory (253) can be implemented using a light bundle. The quantum memory (253) can receive qubits from an information source (251), a quantum operator (252), a quantum measurer (254), an entanglement generator (255), or an optical signal converter (256) and store the corresponding qubits. In addition, the quantum memory (253) can transfer the stored qubits to the information source (251), a quantum operator (252), a quantum measurer (254), an entanglement generator (255), or an optical signal converter (256).

[0407] An entanglement generator (255) generates qubits in an entangled state. The entanglement generator (255) can create new qubits in an entangled state or create qubits in an entangled state using two or more existing qubits. Since information about one qubit among the entangled qubits can be used to obtain information about the other qubit, entangled qubits can play an important role in quantum communication. The entangled qubits generated by the entanglement generator (255) can be stored in a quantum memory (253) or transmitted to an optical signal converter (256) and transmitted through a quantum channel.

[0408] The optical signal converter (256) can convert a qubit into an optical signal or convert an optical signal into a qubit. Here, the qubit can be received from a quantum memory (253) or an entanglement generator (255). The optical signal converter (256) can convert the received qubit into an optical signal, transmit the converted optical signal through a quantum channel, and receive the optical signal. Here, the method of transmitting the optical signal can be performed in various ways. As an example, a quantum direct communication method in which a qubit is converted into a photon and transmitted can be used.

[0409] The quantum communication device is not limited to including all of the components described above in FIG. 40. The quantum communication device may be composed of an information source (251), a quantum operator (252), a quantum measuring device (254), a quantum memory (253), an entanglement generator (255), an optical signal converter (256), and / or a combination thereof, and some components may be combined.

[0410] For example, if a quantum communication device has classical information to transmit, the classical information can be converted into quantum information through an information source (251), and the quantum information can be encoded through a quantum operator (252). The encoded quantum information can be stored in a quantum memory (253), and the quantum information stored in the quantum memory (253) can be transmitted to another device through an optical signal converter (256).

[0411] As another example, a method for performing quantum teleportation based on an entanglement source previously shared between the transmitter and receiver may be utilized. In this case, an entangled state generator may be used to generate a pair of qubits, one of which may be stored in a quantum memory (253), and the other may be transmitted to another device via an optical signal converter (256). Subsequently, classical information may be transmitted by performing message encoding on the qubits stored in the quantum memory (253) using a quantum operator (252).

[0412] When a quantum communication device receives a quantum signal, the quantum signal received through the optical signal converter (256) can be stored in a quantum memory (253) and then measured by a quantum measuring device (254). The measurement result can be transmitted to a control unit. As another example, the quantum communication device can convert the received quantum signal into a qubit and store it in the quantum memory (253). Thereafter, the quantum communication device can convert the qubit stored in the quantum memory (253) into a qubit through a quantum operator (252) and then measure the qubit through a quantum measuring device (254).

[0413] The proposed methods described above can be implemented independently, but they can also be implemented as a combination (or merge) of some of the proposed methods. Rules can be defined so that the base station notifies the terminal of the applicability of the proposed methods (or information about the rules of the proposed methods) through a predefined signal (e.g., a physical layer signal or a higher layer signal).

[0414] The present disclosure may be embodied in other specific forms without departing from the technical ideas and essential features described herein. Therefore, the above detailed description should not be construed as limiting in all respects but rather as illustrative. The scope of the present disclosure should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present disclosure are intended to be included within the scope of the present disclosure. Furthermore, claims that are not explicitly cited in the claims may be combined to form an embodiment or incorporated into a new claim through a post-filing amendment.

[0415] The embodiments described herein may be applied to various wireless access systems. Examples of such wireless access systems include the 3rd Generation Partnership Project (3GPP) or 3GPP2 systems.

[0416] The embodiments described herein can be applied not only to the various wireless access systems described above, but also to all technical fields utilizing these various wireless access systems. Furthermore, the proposed method can be applied to mmWave and THz communication systems utilizing ultra-high frequency bands.

[0417] Additionally, the embodiments can be applied to various applications such as autonomous vehicles and drones.

Claims

1. In a method performed by a first device in a communication system, Step of obtaining system information; A step of performing an initial connection procedure based on the above system information; A step of receiving information about network configuration from a control device; A step of receiving information regarding measurement from the above control device; A step of performing a measurement procedure based on information regarding the above measurement; A step of reporting the measurement results to the above control device; and Including a step of receiving information about a path determined based on the measurement result from the control device, The information regarding the above network configuration includes information indicating the network configuration mode in which the first sub-network is set, The information about the above measurement includes information about the operation mode of the first device that is dynamically set for the first sub-network, A method wherein the above path includes a multi-hop segment that is in at least one maximally entangled state.

2. In paragraph 1, A method wherein the information regarding the measurement comprises at least one of information regarding a classical channel, information regarding a quantum channel, and an identifier and link pairing information of the first sub-network.

3. In paragraph 2, The above measurement result includes whether the transformation of the maximum entangled state of the 2-hop segment including the first device, the second device and the third device is successful, The above path is a method including the above 2-hop segment.

4. In paragraph 3, If the information regarding the above measurement includes the link pairing information, the operation mode of the first device is determined as a repeater mode, A method in which the operation mode of the first device is determined as vertex mode when the information regarding the above measurement does not include the link pairing information.

5. In paragraph 4, The operation mode of the first device is determined as the repeater mode, The above link pairing information includes information about the second device and the third device, The vertex nodes of the above 2-hop segment are composed of the second device and the third device, A method in which the relay node of the above 2-hop segment is configured with the above first device.

6. In paragraph 5, The steps for performing the above measurement procedure are: A step of receiving the second qubit among the first qubit and the second qubit in an entangled state from the second device; A step of receiving the third qubit among the third qubit and the fourth qubit in an entangled state from the third device; A step of performing a Bell state measurement using the second qubit and the third qubit; and A method comprising the step of transmitting a measurement result regarding the bell state measurement to the second device.

7. In paragraph 4, The operation mode of the first device is determined as the vertex mode, The steps for performing the above measurement procedure are: A step of generating a pair of entangled qubits composed of a first qubit and a second qubit; A step of transmitting the second qubit to a second device; A step of receiving a bell state measurement result from the second device; and Including a step of measuring the first qubit based on the above bell state measurement result, The above measurement result includes a measurement result regarding the first qubit, The above bell state measurement result includes information about the bell states of the second qubit and the third qubit, The third qubit is entangled with the fourth qubit stored by the third device.

8. In paragraph 7, The step of measuring the first qubit based on the above bell state measurement result is: A step of determining a measurement operator based on the above bell state measurement result; and A method comprising the step of measuring the first qubit based on the measurement operator.

9. In paragraph 1, Within the above network configuration mode, the first sub-network and the second sub-network are set up, The above operation mode for the above first sub-network is set to undefined, A method in which the operation mode for the second sub-network is set to one of a vertex mode and a repeater mode.

10. In paragraph 9, The above first sub-network and the above second sub-network are determined based on the overall network structure of a triangular lattice structure in which one device forms a link with six neighboring devices, A method in which each of the links included in the above overall network structure is included in only one of the first sub-network or the second sub-network.

11. In paragraph 10, The above first sub-network is configured based on the Kagome lattice structure, The above second sub-network is configured based on a triangular lattice structure, The above Kagome lattice structure is composed of triangular units and hexagonal units composed of single link hops arranged adjacent to each other and continuously. The above triangular lattice structure is a method in which triangular units composed of 2-hop segments are arranged adjacent to each other and continuously.

12. In paragraph 11, A method in which the first sub-network is converted into one of a plurality of rectangular lattice structures based on information about link pairing included in the information about the measurement.

13. In paragraph 12, a step of transmitting a resource allocation request to the control device; and A method further comprising the step of transmitting data to a receiving device through a quantum channel generated based on the path.

14. In paragraph 13, The above resource allocation request includes information about the quality of service (QoS) characteristics of the data, If a first quality of service (QoS) characteristic is required for the above data, the information regarding the measurement includes an identifier of the first sub-network, A method in which information about the measurement includes an identifier of the second sub-network, when a second QoS characteristic is required for the above data.

15. In paragraph 1, A step of transmitting an NTI (network topology information) message including connection information between the first device and a neighboring device to the control device; A step of receiving an NCI (network configuration information) message including information on a plurality of network configuration modes from the control device; Further comprising a step of reporting a link connection diagram to the above control device, A method in which the above link connectivity is determined based on an entangled state between the first device and a neighboring device.

16. In paragraph 15, A method wherein the NCI message includes identification information for the network configuration mode, identification information of at least one sub-network defined in the network configuration mode, an operation mode for each of the at least one sub-network, and neighboring device information of the first device.

17. In a method performed by a control device in a communication system, Step of transmitting system information; Steps to perform initial connection procedures; A step of transmitting information about network configuration to a first device; A step of transmitting information regarding measurement to the first device; A step of receiving a measurement result from the first device; and Including a step of transmitting information about a path determined based on the measurement result to the first device, The information regarding the above network configuration includes information indicating the network configuration mode in which the first sub-network is set, The information about the above measurement includes information about the operation mode of the first device that is dynamically set for the first sub-network, A method wherein the above path includes a multi-hop segment that is in at least one maximally entangled state.

18. In paragraph 17, A method wherein the information regarding the measurement comprises at least one of information regarding a classical channel, information regarding a quantum channel, and an identifier and link pairing information of the first sub-network.

19. In paragraph 18, Further comprising the step of receiving a resource allocation request from the first device, The above resource allocation request includes information about the quality of service (QoS) characteristics of the data, A method in which the first sub-network is determined based on the QoS characteristics of the data.

20. In the first device of the communication system, Transmitter and receiver; and comprising a processor coupled to the above transceiver, The above processor, Obtain system information, Perform the initial connection procedure based on the above system information, Receive information about network configuration from the control device, Receive information about the measurement from the above control device, Perform the measurement procedure based on the information about the above measurement, Report the measurement results to the above control device, Configured to receive information about a path determined based on the measurement results from the above control device, The information regarding the above network configuration includes information indicating the network configuration mode in which the first sub-network is set, The information about the above measurement includes information about the operation mode of the first device that is dynamically set for the first sub-network, The above path is a first device including a multi-hop segment that is in at least one maximally entangled state.

21. In a control device in a communication system, Transmitter and receiver; and comprising a processor coupled to the above transceiver, The above processor, Transmit system information, Perform the initial connection procedure, Transmit information about network configuration to the first device, Transmit information about the measurement to the first device, Receive the measurement results from the first device, Configured to transmit information about a path determined based on the measurement result to the first device, The information regarding the above network configuration includes information indicating the network configuration mode in which the first sub-network is set, The information about the above measurement includes information about the operation mode of the first device that is dynamically set for the first sub-network, A control device wherein the above path includes a multi-hop segment that is in at least one maximally entangled state.

22. In communication devices, At least one processor; At least one computer memory connected to said at least one processor and storing instructions that direct operations when executed by said at least one processor, The above actions are, Step of obtaining system information; A step of performing an initial connection procedure based on the above system information; A step of receiving information about network configuration from a control device; A step of receiving information regarding measurement from the above control device; A step of performing a measurement procedure based on information regarding the above measurement; A step of reporting the measurement results to the above control device; and Including a step of receiving information about a path determined based on the measurement result from the control device, The information regarding the above network configuration includes information indicating the network configuration mode in which the first sub-network is set, The information about the above measurement includes information about the operation mode of the first device that is dynamically set for the first sub-network, A communication device wherein the above path includes a multi-hop segment that is in at least one maximally entangled state.

23. In a non-transitory computer-readable medium storing at least one instruction, comprising at least one instruction executable by the processor, At least one of the above commands causes the device to: Obtain system information, Perform the initial connection procedure based on the above system information, Receive information about network configuration from the control device, Receive information about the measurement from the above control device, Perform the measurement procedure based on the information about the above measurement, Report the measurement results to the above control device, Configured to receive information about a path determined based on the measurement results from the above control device, The information regarding the above network configuration includes information indicating the network configuration mode in which the first sub-network is set, The information about the above measurement includes information about the operation mode of the first device that is dynamically set for the first sub-network, A computer-readable medium wherein the path comprises a multi-hop segment having at least one maximally entangled state.

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