System for searching optimal route for delivery UAV in consideration of connectivity with base station and handoff cost

Abstract

An operation method of a terminal, according to the present disclosure, for determining a movement route of a terminal in a wireless communication system, comprises the steps of: transmitting a setup request signal to a first base station; receiving a setup response signal from the first base station on the basis of the setup request signal; setting a movement route on the basis of the setup response signal; receiving a reference signal from a second base station; and transmitting a measurement report to the second base station on the basis of the reference signal, wherein the movement route is determined on the basis of a handover cost and a connectable range in which the terminal can perform communication for at least one base station, wherein the connectable range can be updated through the measurement report.

Description

An optimal route search system for delivery UAVs considering connectivity with base stations and handoff costs.

[0001] The following description relates to a wireless communication system, and to a device and method for determining a movement path of a terminal based on connectivity with a base station and handover costs 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 can provide a device and method for determining a movement path of a terminal based on connectivity with a base station and handover cost in a wireless communication system.

[0005] The present disclosure can provide a device and method for determining a movement path of a terminal based on measurement information measured based on a reference signal in a wireless communication system.

[0006] The present disclosure can provide a device and method for determining a movement path of a terminal based on an intersection of boundaries of a base station's connectable range in a wireless communication system.

[0007] The present disclosure can provide a device and method for determining an optimal movement path by considering the number of handovers and movement time in a wireless communication system.

[0008] The present disclosure can provide a device and method for a control center connected through a backhaul network in a wireless communication system to determine a movement path of a terminal.

[0009] The present disclosure can provide a device and method for theoretically determining a movement path of a terminal in a wireless communication system.

[0010] The present disclosure may provide a device and method for updating parameter values ​​for determining a movement path in a wireless communication system.

[0011] The present disclosure can provide a device and method for determining a movement path with a minimum number of handovers in a wireless communication system.

[0012] The present disclosure can provide a device and method for determining a movement path based on the weights of edges forming a graph in a wireless communication system.

[0013] The present disclosure may provide a device and method for transporting a person or object in a wireless communication system.

[0014] The present disclosure relates to a device and method for transmitting a plurality of transport blocks (TBs) as a single unit in a wireless communication system.

[0015] 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.

[0016] As an example of the present disclosure, a method of operating a terminal in a wireless communication system includes the steps of transmitting a configuration request signal to a first base station, receiving a configuration response signal from the first base station based on the configuration request signal, setting a movement path based on the configuration response signal, receiving a reference signal from a second base station, and transmitting a measurement report to the second base station based on the reference signal, wherein the movement path is determined based on a connectable range and a handover cost in which the terminal can perform communication for each of at least one base station, and the connectable range can be updated through the measurement report.

[0017] As an example of the present disclosure, a method for operating a first base station in a wireless communication system includes the steps of: receiving a setup request signal from a terminal; determining a movement path based on the setup request signal; transmitting a setup response signal including information about the movement path to the terminal; receiving a measurement report measured by the terminal from a second base station; and updating a parameter value for determining the movement path based on the measurement report, wherein the movement path is determined based on a connectable range and a handover cost in which the terminal can perform communication with respect to at least one base station, and the connectable range can be updated through the measurement report.

[0018] As an example of the present disclosure, a terminal in a wireless communication system includes a transceiver and a processor connected to the transceiver, wherein the processor controls to transmit a setup request signal to a first base station, receive a setup response signal from the first base station based on the setup request signal, set a movement path based on the setup response signal, receive a reference signal from a second base station, and transmit a measurement report to the second base station based on the reference signal, wherein the movement path is determined based on a connectable range and a handover cost in which the terminal can perform communication for each of at least one base station, and the connectable range can be updated through the measurement report.

[0019] As an example of the present disclosure, in a wireless communication system, a first base station includes a transceiver and a processor connected to the transceiver, wherein the processor receives a configuration request signal from a terminal, determines a movement path based on the configuration request signal, transmits a configuration response signal including information about the movement path to the terminal, receives a measurement report measured by the terminal from a second base station, and controls updating parameter values ​​for determining the movement path based on the measurement report, wherein the movement path is determined based on a connectable range and a handover cost in which the terminal can perform communication with respect to at least one base station, and the connectable range can be updated through the measurement report.

[0020] 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 direct operations when executed by the at least one processor, the operations including: transmitting a configuration request signal to a first base station; receiving a configuration response signal from the first base station based on the configuration request signal; setting a movement path based on the configuration response signal; receiving a reference signal from a second base station; and transmitting a measurement report to the second base station based on the reference signal, wherein the movement path is determined based on a connectable range and a handover cost in which the communication device can perform communication with respect to each of the at least one base station, and the connectable range can be updated through the measurement report.

[0021] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction, the at least one instruction being executable by a processor, the at least one instruction controlling a device to transmit a setup request signal to a first base station, receive a setup response signal from the first base station based on the setup request signal, set a moving path based on the setup response signal, receive a reference signal from a second base station, and transmit a measurement report to the second base station based on the reference signal, wherein the moving path is determined based on a connectable range and a handover cost over which the device can perform communication for each of at least one base station, and the connectable range can be updated through the measurement report.

[0022] 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.

[0023] The following effects may be achieved by embodiments based on the present disclosure.

[0024] According to the present disclosure, a movement path of a terminal can be efficiently determined based on connectivity with a base station and handover costs in a wireless communication system.

[0025] According to the present disclosure, a movement path of a terminal can be determined with low complexity in a wireless communication system.

[0026] According to the present disclosure, it is possible to search for a terminal's movement path that minimizes handover costs.

[0027] According to the present disclosure, a movement path of a terminal can be determined by utilizing a graph generated based on the coverage radius of a base station.

[0028] According to the present disclosure, the movement path of a terminal can be determined using the GIM-HO (generalized intersection method with hand-off, GIM-HO) technique.

[0029] The effects that can be obtained from the embodiments of the present disclosure are not limited to the effects mentioned above, and other effects that are 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 that result from implementing the configuration described in the present disclosure can also be derived by those skilled in the art from the embodiments of the present disclosure.

[0030] The accompanying drawings are intended to aid in understanding 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.

[0031] FIG. 1 is a diagram illustrating an example of a communication system applicable to the present disclosure.

[0032] FIG. 2 is a drawing showing an example of a wireless device applicable to the present disclosure.

[0033] FIG. 3 is a diagram showing another example of a wireless device applicable to the present disclosure.

[0034] FIG. 4 is a drawing showing an example of a mobile device applicable to the present disclosure.

[0035] FIG. 5 is a drawing showing an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0036] Figure 6 is a diagram showing an example of AI (Artificial Intelligence) applicable to the present disclosure.

[0037] FIG. 7 is a diagram illustrating a method for processing a transmission signal applicable to the present disclosure.

[0038] FIG. 8 is a diagram showing an example of a communication structure that can be provided in a 6G system applicable to the present disclosure.

[0039] Figure 9 is a diagram showing an electromagnetic spectrum applicable to the present disclosure.

[0040] Fig. 10 is a diagram showing a THz communication method applicable to the present disclosure.

[0041] FIG. 11 illustrates an example of a transport environment of a UAV according to one embodiment of the present disclosure.

[0042] FIG. 12 illustrates an example of a path along which a UAV performs a transport task according to one embodiment of the present disclosure.

[0043] FIG. 13 illustrates an example of an operation procedure of a generalized intersection method with hand-off (GIM-HO) technique according to one embodiment of the present disclosure.

[0044] FIG. 14 illustrates an example of an optimal base station connection strategy corresponding to a given path according to one embodiment of the present disclosure.

[0045] FIG. 15 illustrates an example of a method for a terminal to receive an optimized movement path according to one embodiment of the present disclosure.

[0046] FIG. 16 illustrates an example of a procedure in which a control center transmits a movement path to a terminal according to one embodiment of the present disclosure.

[0047] FIG. 17 illustrates an example of signaling for optimizing a movement path by a terminal according to one embodiment of the present disclosure.

[0048] FIG. 18 illustrates an example of signaling for a core network to optimize a movement path and transmit the optimized path to a first terminal according to one embodiment of the present disclosure.

[0049] Figure 19 illustrates an example of simulation results in a real environment according to one embodiment of the present disclosure.

[0050] FIG. 20 illustrates an example of searching for a path from a starting point to an arrival point where connectivity of base stations is maintained according to one embodiment of the present disclosure.

[0051] FIG. 21 illustrates an example of a path search result by handover cost using the GIM-HO technique according to one embodiment of the present disclosure.

[0052] The following embodiments combine 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.

[0053] 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.

[0054] 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.

[0055] 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.

[0056] 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.

[0057] Additionally, in 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).

[0058] 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.

[0059] 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 5G (5th generation) 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.

[0060] Furthermore, the embodiments of the present disclosure may be applied to other wireless access systems and are not limited to the aforementioned systems. For example, they may be applicable to systems implemented after the 3GPP 5G NR system, and are not limited to a specific system.

[0061] 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.

[0062] 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.

[0063] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding 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.

[0064] 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).

[0065] In order to make the following description clear, the following description is based on a 3GPP communication system (e.g., LTE, NR, etc.), but the technical idea of ​​the present invention 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.

[0066] For background information, terms, abbreviations, etc. used in this disclosure, reference may be made to standard documents published prior to the invention of the present invention. For example, reference may be made to the 36.xxx and 38.xxx standard documents.

[0067] Communication system applicable to the present disclosure

[0068] 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.

[0069] 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.

[0070] FIG. 1 is a diagram illustrating an example of a communication system applied to the present disclosure.

[0071] 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., 5G NR, LTE) 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.

[0072] 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) network, etc. 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). In addition, IoT devices (100f) (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0073] 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 (e.g., 5G NR) 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.

[0074] Communication system applicable to the present disclosure

[0075] FIG. 2 is a diagram illustrating an example of a wireless device applicable to the present disclosure.

[0076] Referring to FIG. 2, the first wireless device (200a) and the second wireless device (200b) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (200a), the second wireless device (200b)} can correspond to {the wireless device (100x), the base station (120)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 1.

[0077] A first wireless device (200a) includes one or more processors (202a) and one or more memories (204a), and may further include one or more transceivers (206a) and / or one or more antennas (208a). The processor (202a) controls the memories (204a) and / or the transceivers (206a), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202a) may process information in the memory (204a) to generate first information / signals, and then transmit a wireless signal including the first information / signals via the transceivers (206a). In addition, the processor (202a) may receive a wireless signal including second information / signals via the transceivers (206a), and then store information obtained from signal processing of the second information / signals in the memory (204a). The memory (204a) may be connected to the processor (202a) and may store various information related to the operation of the processor (202a). For example, the memory (204a) may perform some or all of the processes controlled by the processor (202a), or may store software code including instructions for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. Here, the processor (202a) and the memory (204a) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206a) may be connected to the processor (202a) and may transmit and / or receive wireless signals via one or more antennas (208a). The transceiver (206a) may include a transmitter and / or a receiver. The transceiver (206a) 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.

[0078] The second wireless device (200b) includes one or more processors (202b), one or more memories (204b), and may further include one or more transceivers (206b) and / or one or more antennas (208b). The processor (202b) controls the memories (204b) and / or the transceivers (206b), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202b) may process information in the memory (204b) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206b). In addition, the processor (202b) may receive a wireless signal including fourth information / signals via the transceivers (206b), and then store information obtained from the signal processing of the fourth information / signals in the memory (204b). The memory (204b) may be connected to the processor (202b) and may store various information related to the operation of the processor (202b). For example, the memory (204b) may perform some or all of the processes controlled by the processor (202b), or may store software code including instructions for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. Here, the processor (202b) and the memory (204b) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206b) may be connected to the processor (202b) and may transmit and / or receive wireless signals via one or more antennas (208b). The transceiver (206b) may include a transmitter and / or a receiver. The transceiver (206b) may be used interchangeably with an RF unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0079] Hereinafter, hardware elements of the wireless device (200a, 200b) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (202a, 202b). For example, one or more processors (202a, 202b) may implement one or more layers (e.g., functional layers such as physical (PHY), media access control (MAC), radio link control (RLC), packet data convergence protocol (PDCP), radio resource control (RRC), and service data adaptation protocol (SDAP)). One or more processors (202a, 202b) may generate one or more Protocol Data Units (PDUs) and / or one or more Service Data Units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. One or more processors (202a, 202b) may generate messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein. One or more processors (202a, 202b) may generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed herein, and provide the signals to one or more transceivers (206a, 206b). One or more processors (202a, 202b) may receive signals (e.g., baseband signals) from one or more transceivers (206a, 206b) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein.

[0080] One or more processors (202a, 202b) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (202a, 202b) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more digital signal processing devices (DSPDs), one or more programmable logic devices (PLDs), or one or more field programmable gate arrays (FPGAs) may be included in one or more processors (202a, 202b). The descriptions, functions, procedures, proposals, methods, and / or operational 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, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software configured to perform one or more processors (202a, 202b) or stored in one or more memories (204a, 204b) and executed by one or more processors (202a, 202b). The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0081] One or more memories (204a, 204b) may be coupled to one or more processors (202a, 202b) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (204a, 204b) may be configured as read only memory (ROM), random access memory (RAM), erasable programmable read only memory (EPROM), flash memory, hard drives, registers, cache memory, computer readable storage media, and / or combinations thereof. The one or more memories (204a, 204b) may be located internally and / or externally to the one or more processors (202a, 202b). Additionally, the one or more memories (204a, 204b) may be coupled to the one or more processors (202a, 202b) via various technologies, such as wired or wireless connections.

[0082] One or more transceivers (206a, 206b) can transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or flowcharts of this document, to one or more other devices. One or more transceivers (206a, 206b) can receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts of this document, from one or more other devices. For example, one or more transceivers (206a, 206b) can be coupled to one or more processors (202a, 202b) and can transmit and receive wireless signals. For example, one or more processors (202a, 202b) can control one or more transceivers (206a, 206b) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (202a, 202b) may control one or more transceivers (206a, 206b) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (206a, 206b) may be coupled to one or more antennas (208a, 208b), and one or more transceivers (206a, 206b) may be configured to transmit and receive user data, control information, wireless signals / channels, or the like, as referred to in the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document, via one or more antennas (208a, 208b). In this document, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers (206a, 206b) can convert received user data, control information, 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 one or more processors (202a, 202b).One or more transceivers (206a, 206b) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (202a, 202b) from baseband signals to RF band signals. For this purpose, one or more transceivers (206a, 206b) may include an (analog) oscillator and / or filter.

[0083] Wireless device structure applicable to the present disclosure

[0084] FIG. 3 is a diagram illustrating another example of a wireless device applicable to the present disclosure.

[0085] Referring to FIG. 3, the wireless device (300) corresponds to the wireless devices (200a, 200b) of FIG. 2 and may be composed of various elements, components, units, and / or modules. For example, the wireless device (300) may include a communication unit (310), a control unit (320), a memory unit (330), and additional elements (340). The communication unit may include a communication circuit (312) and a transceiver(s) (314). For example, the communication circuit (312) may include one or more processors (202a, 202b) and / or one or more memories (204a, 204b) of FIG. 2. For example, the transceiver(s) (314) may include one or more transceivers (206a, 206b) and / or one or more antennas (208a, 208b) of FIG. 2. The control unit (320) is electrically connected to the communication unit (310), the memory unit (330), and the additional elements (340) and controls the overall operation of the wireless device. For example, the control unit (320) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (330). In addition, the control unit (320) may transmit information stored in the memory unit (330) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (310), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (330).

[0086] The additional element (340) may be configured in various ways depending on the type of the wireless device. For example, the additional element (340) may include at least one of a power unit / battery, an input / output unit, a driving unit, and a computing unit. Although not limited thereto, the wireless device (300) 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, 140), a base station (Fig. 1, 120), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0087] In FIG. 3, various elements, components, units / parts, and / or modules within the wireless device (300) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (310). For example, within the wireless device (300), the control unit (320) and the communication unit (310) may be wired, and the control unit (320) and the first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (310). In addition, each element, component, unit / part, and / or module within the wireless device (300) may further include one or more elements. For example, the control unit (320) may be composed of a set of one or more processors. For example, the control unit (320) 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 (330) may be composed of RAM, DRAM (dynamic RAM), ROM, flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0088] Mobile devices to which the present disclosure applies

[0089] FIG. 4 is a drawing illustrating an example of a mobile device applied to the present disclosure.

[0090] Figure 4 illustrates an example of a mobile device applicable to the present disclosure. The mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), or a portable computer (e.g., a laptop, etc.). The mobile device may be referred to as a mobile station (MS), a user terminal (UT), a mobile subscriber station (MSS), a subscriber station (SS), an advanced mobile station (AMS), or a wireless terminal (WT).

[0091] Referring to FIG. 4, the portable device (400) may include an antenna unit (408), a communication unit (410), a control unit (420), a memory unit (430), a power supply unit (440a), an interface unit (440b), and an input / output unit (440c). The antenna unit (408) may be configured as a part of the communication unit (410). Blocks 410 to 430 / 440a to 440c correspond to blocks 310 to 330 / 340 of FIG. 3, respectively.

[0092] The communication unit (410) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (420) can control components of the portable device (400) to perform various operations. The control unit (420) can include an AP (application processor). The memory unit (430) can store data / parameters / programs / codes / commands required for operating the portable device (400). In addition, the memory unit (430) can store input / output data / information, etc. The power supply unit (440a) supplies power to the portable device (400) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (440b) can support connection between the portable device (400) and other external devices. The interface unit (440b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (440c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (440c) may include a camera, a microphone, a user input unit, a display unit (440d), a speaker, and / or a haptic module.

[0093] For example, in the case of data communication, the input / output unit (440c) 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 (430). The communication unit (410) can convert the information / signals stored in the memory into wireless signals, and transmit the converted wireless signals directly to other wireless devices or to a base station. In addition, the communication unit (410) 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 (430) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (440c).

[0094] Types of wireless devices to which the present disclosure applies

[0095] FIG. 5 is a drawing illustrating an example of a vehicle or autonomous vehicle to which the present disclosure applies.

[0096] Figure 5 illustrates a vehicle or autonomous vehicle applicable to the present disclosure. The vehicle or autonomous vehicle may be implemented as a mobile robot, car, train, manned / unmanned aerial vehicle (AV), ship, etc., and is not limited to the form of a vehicle.

[0097] Referring to FIG. 5, a vehicle or autonomous vehicle (500) may include an antenna unit (508), a communication unit (510), a control unit (520), a driving unit (540a), a power supply unit (540b), a sensor unit (540c), and an autonomous driving unit (540d). The antenna unit (550) may be configured as a part of the communication unit (510). Blocks 510 / 530 / 540a to 540d correspond to blocks 410 / 430 / 440 of FIG. 4, respectively.

[0098] The communication unit (510) 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, etc.), servers, etc. The control unit (520) can control elements of a vehicle or autonomous vehicle (500) to perform various operations. The control unit (520) can include an electronic control unit (ECU).

[0099] Figure 6 is a diagram illustrating an example of an AI device applicable to the present disclosure. For example, the AI ​​device may be implemented as a fixed or mobile device, such as a TV, projector, smartphone, PC, laptop, digital broadcasting terminal, tablet PC, wearable device, set-top box (STB), radio, washing machine, refrigerator, digital signage, robot, or vehicle.

[0100] Referring to FIG. 6, the AI ​​device (600) may include a communication unit (610), a control unit (620), a memory unit (630), an input / output unit (640a / 640b), a learning processor unit (640c), and a sensor unit (640d). Blocks 610 to 630 / 640a to 640d may correspond to blocks 310 to 330 / 340 of FIG. 3, respectively.

[0101] The communication unit (610) 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., FIG. 1, 100x, 120, 140) or AI servers (FIG. 1, 140) using wired and wireless communication technology. To this end, the communication unit (610) can transmit information within the memory unit (630) to the external device or transfer a signal received from the external device to the memory unit (630).

[0102] The control unit (620) may determine at least one executable operation of the AI ​​device (600) based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the control unit (620) may control components of the AI ​​device (600) to perform the determined operation. For example, the control unit (620) may request, search, receive, or utilize data from the learning processor unit (640c) or the memory unit (630), and may control components of the AI ​​device (600) to perform a predicted operation or an operation determined to be desirable among at least one executable operation. In addition, the control unit (620) may collect history information including the operation contents of the AI ​​device (600) or user feedback on the operation, and store the collected history information in the memory unit (630) or the learning processor unit (640c), or transmit the collected history information to an external device such as an AI server (FIG. 1, 140). The collected history information may be used to update a learning model.

[0103] The memory unit (630) can store data that supports various functions of the AI ​​device (600). For example, the memory unit (630) can store data obtained from the input unit (640a), data obtained from the communication unit (610), output data of the learning processor unit (640c), and data obtained from the sensing unit (640). In addition, the memory unit (630) can store control information and / or software codes necessary for the operation / execution of the control unit (620).

[0104] The input unit (640a) can obtain various types of data from the outside of the AI ​​device (600). For example, the input unit (620) can obtain learning data for model learning, input data to which the learning model will be applied, etc. The input unit (640a) may include a camera, a microphone, and / or a user input unit. The output unit (640b) may generate output related to vision, hearing, or touch. The output unit (640b) may include a display unit, a speaker, and / or a haptic module, etc. The sensing unit (640) can obtain at least one of internal information of the AI ​​device (600), information about the surrounding environment of the AI ​​device (600), and user information using various sensors. The sensing unit (640) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar, etc.

[0105] The learning processor unit (640c) can train a model composed of an artificial neural network using learning data. The learning processor unit (640c) can perform AI processing together with the learning processor unit of the AI ​​server (Fig. 1, 140). The learning processor unit (640c) can process information received from an external device via the communication unit (610) and / or information stored in the memory unit (630). In addition, the output value of the learning processor unit (640c) can be transmitted to an external device via the communication unit (610) and / or stored in the memory unit (630).

[0106] FIG. 7 is a diagram illustrating a method for processing a transmission signal applied to the present disclosure. For example, the transmission signal may be processed by a signal processing circuit. At this time, the signal processing circuit (700) may include a scrambler (710), a modulator (720), a layer mapper (730), a precoder (740), a resource mapper (750), and a signal generator (760). At this time, as an example, the operations / functions of FIG. 7 may be performed in the processors (202a, 202b) and / or the transceivers (206a, 206b) of FIG. 2. Furthermore, as an example, the hardware elements of FIG. 7 may be implemented in the processors (202a, 202b) and / or the transceivers (206a, 206b) of FIG. 2. As an example, blocks 710 to 760 may be implemented in the processors (202a, 202b) of FIG. 2. Additionally, blocks 710 to 750 may be implemented in the processor (202a, 202b) of FIG. 2, and block 760 may be implemented in the transceiver (206a, 206b) of FIG. 2, and are not limited to the above-described embodiments.

[0107] The codeword can be converted into a wireless signal through the signal processing circuit (700) of FIG. 7. 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). The wireless signal may be transmitted through various physical channels (e.g., a PUSCH, a PDSCH). Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (710). 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 can be modulated into a modulation symbol sequence by a modulator (720). The modulation scheme may include pi / 2-binary phase shift keying (pi / 2-BPSK), m-phase shift keying (m-PSK), m-quadrature amplitude modulation (m-QAM), etc.

[0108] A complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (730). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (740) (precoding). The output z of the precoder (740) can be obtained by multiplying the output y of the layer mapper (730) by an N*M precoding matrix W. Here, N is the number of antenna ports, and M is the number of transmission layers. Here, the precoder (740) can perform precoding after performing transform precoding (e.g., discrete Fourier transform (DFT) transform) on the complex modulation symbols. In addition, the precoder (740) can perform precoding without performing transform precoding.

[0109] The resource mapper (750) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. The signal generator (760) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (760) can include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, and the like.

[0110] The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (710 to 760) of FIG. 7. For example, a wireless device (e.g., 200a and 200b of FIG. 2) can receive wireless signals from the outside through an antenna port / transceiver. The received wireless signals can be converted into baseband signals through a signal restorer. For this purpose, the signal restorer can 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 can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codewords can be restored to the original information blocks through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0111] 6G communication system

[0112] The 6G (wireless communication) system aims to achieve (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) low energy consumption for 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 satisfy the requirements as shown in Table 1 below. In other words, Table 1 is a table showing the requirements of the 6G system.

[0113] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0114] 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.

[0115] FIG. 8 is a diagram illustrating an example of a communication structure that can be provided in a 6G system applicable to the present disclosure.

[0116] Referring to Figure 8, 6G systems are expected to have 50 times higher simultaneous wireless connectivity than 5G wireless systems. URLLC, a key feature of 5G, is expected to become a more prominent technology in 6G communications, providing end-to-end latency of less than 1 ms. Furthermore, 6G systems will have significantly better volumetric spectral efficiency, unlike 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.

[0117] Core implementation technology of 6G systems

[0118] - Artificial Intelligence (AI)

[0119] The most crucial and newly introduced technology for 6G systems is AI. 4G systems did not involve AI. 5G systems will support partial or very limited AI. However, 6G systems will fully support AI for automation. Advances in machine learning will create more intelligent networks for real-time communications in 6G. Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analyses to determine how complex target tasks should be performed. In other words, AI can increase efficiency and reduce processing delays.

[0120] Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly using AI. AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. Furthermore, AI can facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0121] Recent attempts to integrate AI into wireless communication systems have focused on the application layer and network layer, particularly deep learning in wireless resource management and allocation. However, this research is increasingly evolving to the MAC layer and physical layer, with attempts to combine deep learning with wireless transmission, particularly in the physical layer. AI-based physical layer transmission refers to applying AI-based signal processing and communication mechanisms, rather than traditional communication frameworks, in the fundamental signal processing and communication mechanisms. For example, this may include deep learning-based channel coding and decoding, deep learning-based signal estimation and detection, deep learning-based multiple input multiple output (MIMO) mechanisms, and AI-based resource scheduling and allocation.

[0122] Machine learning can be used for channel estimation and channel tracking, as well as for power allocation and interference cancellation at the physical layer of the downlink (DL). Machine learning can also be used for antenna selection, power control, and symbol detection in MIMO systems.

[0123] However, the application of DNN for transmission at the physical layer may have the following problems.

[0124] Deep learning-based AI algorithms require a large amount of training data to optimize training parameters. However, due to limitations in obtaining training data from specific channel environments, a large amount of training data is used offline. This means that static training on training data in specific channel environments can lead to conflicts with the dynamic characteristics and diversity of the wireless channel.

[0125] Furthermore, current deep learning primarily targets real-world signals. However, signals at the physical layer of wireless communications are complex signals. Further research is needed on neural networks capable of detecting complex domain signals to match the characteristics of wireless communication signals.

[0126] Below, we will look at machine learning in more detail.

[0127] Machine learning refers to a series of operations that train machines to perform tasks that humans can or cannot perform. Machine learning requires data and a learning model. In machine learning, data learning methods can be broadly categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.

[0128] Neural network training aims to minimize output errors. It involves repeatedly inputting training data into a neural network, calculating the neural network output and target error for the training data, and backpropagating the neural network error from the output layer to the input layer to update the weights of each node in the neural network to reduce the error.

[0129] Supervised learning uses labeled training data, while unsupervised learning may not have labeled training data. For example, in the case of supervised learning for data classification, the training data may be data in which each training data category is labeled. Labeled training data is input to a neural network, and the error can be calculated by comparing the output (categories) of the neural network with the training data labels. The calculated error is backpropagated through the neural network in the backward direction (i.e., from the output layer to the input layer), and the connection weights of each node in each layer of the neural network can be updated according to the backpropagation. The amount of change in the connection weights of each updated node can be determined by the learning rate. The neural network's calculation of the input data and the backpropagation of the error can constitute a learning cycle (epoch). The learning rate can be applied differently depending on the number of iterations of the neural network's learning cycle. For example, in the early stages of training a neural network, a high learning rate can be used to quickly allow the network to reach a certain level of performance, thereby improving efficiency. In the later stages of training, a low learning rate can be used to improve accuracy.

[0130] Learning methods may vary depending on the characteristics of the data. For example, if the goal is to accurately predict data transmitted by a transmitter in a communication system, supervised learning is preferable to unsupervised learning or reinforcement learning.

[0131] The learning model corresponds to the human brain, and the most basic linear model can be thought of, but the machine learning paradigm that uses highly complex neural network structures, such as artificial neural networks, as learning models is called deep learning.

[0132] The neural network cores used in learning methods are largely divided into deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent Boltzmann machines (RNN), and these learning models can be applied.

[0133] THz (Terahertz) communication

[0134] THz communications can be applied in 6G systems. For example, data transmission rates can be increased by increasing bandwidth. This can be achieved by using sub-THz communications with wide bandwidths and applying advanced massive MIMO technology.

[0135] FIG. 9 is a diagram illustrating an electromagnetic spectrum applicable to the present disclosure. For example, referring to FIG. 9, THz waves, also known as sub-millimeter radiation, typically represent a frequency band between 0.1 THz and 10 THz with a corresponding wavelength ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (Sub-THz band) is considered a major portion of the THz band for cellular communications. Adding the Sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz to 3 THz is in the far infrared (IR) frequency band. Although the 300 GHz to 3 THz band is part of the optical band, it is at the boundary of the optical band and lies just behind the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF.

[0136] Key characteristics of THz communications include (i) the widely available bandwidth to support very high data rates and (ii) the high path loss that occurs at high frequencies (requiring highly directional antennas). The narrow beamwidths generated by highly directional antennas reduce interference. The small wavelength of THz signals allows for a significantly larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.

[0137] Terahertz (THz) wireless communications

[0138] FIG. 10 is a diagram illustrating a THz communication method applicable to the present disclosure.

[0139] Referring to Fig. 10, THz wireless communication is a wireless communication using THz waves with a frequency of approximately 0.1 to 10 THz (1 THz = 1012 Hz), and may refer to terahertz (THz) band wireless communication using a very high carrier frequency of 100 GHz or higher. THz waves are located between the RF (Radio Frequency) / millimeter (mm) and infrared bands, and (i) compared to visible light / infrared rays, they penetrate non-metallic / non-polarizable materials well, and compared to RF / millimeter waves, they have a shorter wavelength, so they have high straightness and can enable beam focusing.

[0140] Specific embodiments of the present invention

[0141] Transportation services utilizing air transport could be implemented in urban areas. Urban air mobility (UAM) primarily aims to rapidly transport people and goods within cities using small aircraft or drones. UAM can be operated by integrating various cutting-edge technologies, including autonomous flight technology, electric propulsion systems, and advanced air traffic management systems.

[0142] For convenience of explanation, the following describes a method for operating an unmanned aerial vehicle (UAV). However, the method applied to the present disclosure is not limited to UAVs. In other words, it can be applied to any terminal that determines a movement path using wireless communication, such as a drone, manned aircraft, or autonomous vehicle.

[0143] Unmanned aerial vehicles (UAVs) offer a wide range of applications due to their freedom of movement and low cost. They can be used for a variety of purposes, including transportation, data collection from flying base stations and IoT devices, and for reconnaissance during military operations or onboard warships. Remotely controlling UAVs requires establishing a communications network and establishing procedures for controlling the UAV.

[0144] When a UAV transports people or delivers goods, its path can be set to travel from the starting point to the destination in the shortest possible time. However, for safety reasons and route updates, the UAV must maintain a connection with a ground base station during its flight. Therefore, while it is important for operators to determine the shortest distance or travel time for the UAV's path, they must also consider features that prevent loss of communication with the control center due to factors such as route loss and line-of-sight (LoS). To address these issues, operators can design the UAV to utilize cellular communications. The UAV can communicate with a nearby base station. The UAV can then connect to the control center via a backhaul network via the connected base station. The base stations can act as relays for the connection between the UAV and the control center. Therefore, operators must devise a method for the UAV to find an optimal path while maintaining communication with the base station using cellular communications.

[0145] Reinforcement learning, a type of machine learning, can be used to determine optimal movement paths. Reinforcement learning is a learning method that enables optimal behavior in a given environment. An agent performs a specific action in a given environment and receives a reward and the next state as a result. Based on the reward, the agent can modify its behavioral pattern, perform a new action, and receive a reward. By repeating this process, the agent can achieve the behavior that yields the optimal reward. UAVs can also perform reinforcement learning as agents. The reward in reinforcement learning relates to the UAV's movement and can be set as a value for optimal path search. Reinforcement learning-based path search technology has the advantage of enabling path search even in situations where there is little prior information about the communication environment. However, reinforcement learning-based path search technology cannot always guarantee optimal paths, and its high complexity consumes significant computing resources.

[0146] To address the limitations of path finding techniques using reinforcement learning, path finding techniques utilizing theoretical methods can be proposed. A theoretical approach involves setting variables and mathematical formulas for problem solving, using these formulas as objective functions to find a solution that maximizes them, or finding a solution to a specific equation. Representative examples of theoretical approaches include convex optimization, graph theory, and dynamic programming. These approaches typically have lower complexity than approaches using reinforcement learning.

[0147] To simplify the problem, we can determine the distance at which a UAV can maintain a communication connection with a base station, and assume that the UAV can maintain a communication connection with the base station if the distance is less than or equal to a certain threshold distance value. Therefore, the problem of maintaining UAV connectivity and finding a path can be solved using convex optimization or graph theory. Convex optimization is a method of finding the values ​​of variables that minimize or maximize a given convex function. To perform convex optimization, a gradient-based approach can be used to determine the point where the convex function is maximized or minimized within a specific range. Representative methods that use convex optimization or graph theory include exhaustive search (ES), exhaustive search with fixed association (ES-FA), and exhaustive search with quantization (ES-Q).

[0148] The ES technique is a convex optimization-based search method that searches all possible paths, and has a high complexity of NP-hard. The ES-FA technique performs similarly to the ES technique, but the complexity can be reduced by considering the path while fixing the order of visiting base stations. The ES-Q technique is a method for searching the path based on a graph whose vertices are quantized points in the overlapping area where connectivity can be maintained between each base station pair. The ES-Q technique compresses the graph form into a finite number of points and lines that are important in path search by simplifying cellular communication and movement paths. The ES-FA and ES-Q techniques have a complexity of NP-easy, but do not guarantee an optimal path.

[0149] The node method is a graph-theory-based path finding method that uses a finite number of nodes, each defined by the boundaries of the communication range between each base station, as vertices. The node method compresses the communication and mobility environment into a graph and fixes the order in which base stations are visited. Therefore, the node method has NP-easy complexity, but does not guarantee optimal paths. Furthermore, path finding techniques that consider communication interruption periods, consider multi-UAV collaboration, and utilize 3D building maps and 3D radio maps are being considered.

[0150] Finding the optimal path in a graph-transformed environment can be accomplished using Dijkstra's algorithm. Dijkstra's algorithm is an algorithm that searches for the shortest path between vertices in a graph. It is widely used in satellites and the Global Positioning System (GPS). Dijkstra's algorithm exploits the fact that the shortest path is composed of the sum of multiple sub-shortest paths. Therefore, Dijkstra's algorithm updates the currently known shortest path rather than searching all paths. Because Dijkstra's algorithm can be implemented with low complexity, it can be efficiently used even for large graphs.

[0151] However, the above-described techniques have the disadvantage of not being able to find the optimal path, or having a high complexity that is NP-hard when finding the optimal path. In addition, the above-described techniques do not consider the loss caused by handover between base stations when finding the path. However, highly mobile entities such as UAVs and autonomous vehicles can experience communication performance degradation due to handover, and the frequency of disconnection from base stations increases, so such loss must be considered when finding the path. Here, handover refers to the procedure for a specific device to change base stations to maintain a communication connection when a base station must be changed due to reasons such as channel deterioration. Handover can be referred to by other terms such as handoff and is not limited to a specific name.

[0152] The present disclosure proposes a method for a UAV to maintain connectivity with a base station in a cellular network while performing a transport mission from a starting point to a destination. Referring to the present disclosure, the UAV can perform the transport mission using an optimal route determined by considering the cost of handover. Furthermore, the present disclosure proposes an optimal path search method with NP-easy complexity for determining the optimal path search.

[0153] FIG. 11 illustrates an example of a transport environment of a UAV (1110) according to one embodiment of the present disclosure. Referring to FIG. 11, one can understand the communication environment that may change along the route of a UAV (1110) transporting goods from a starting point to a destination, and determine the meaning of parameter values ​​to be used below.

[0154] For the convenience of explanation, a three-dimensional coordinate notation consisting of the x-axis, y-axis, and z-axis is used to indicate the location in the following. In addition, the UAV (1110) starts from a terrestrial cellular network where M base stations (1120#1 to 1120#3) exist. From the arrival point Assume that you are performing a mission to deliver goods to . The second base station is It is assumed that all base stations are connected to a control center (1130) that can remotely control the UAV (1110) through a backhaul network, etc. At this time, the control center (1130) can determine the movement path of the UAV (1110).

[0155] UAV (1110) must maintain a connection with at least one base station to perform transportation tasks. The present disclosure is a visual The location of the UAV (1110) is It is to be expressed as . Also, the speed of UAV (1110) is , the horizontal coordinate of the starting point is , the horizontal coordinate of the Mth base station (1120#M) is , the horizontal coordinates of the arrival point are and visual Location of UAV (1110) in It is expressed as .

[0156] In downlink communication, the UAV (1110) receives a signal from a base station when the SINR (signal to interference plus noise ratio) value is lower than a specific threshold value. In this case, it can be connected to the base station. In addition, in the uplink communication situation, the UAV (1110) can be connected to the base station if the SINR of the signal received by the base station is above a certain threshold value. The channel between the UAV (1110) and the base stations (1120#1 to 1120#3) can be assumed as a LoS path acquisition probability model. In the LoS path acquisition probability, the channel environment considers only large-scale fading. Here, large-scale fading mainly refers to a frequency change caused by geographical dispersion, absorption or scattering due to obstacles such as buildings and trees when a signal is transmitted from a transmitter to a receiver.

[0157] In the LoS path acquisition probability model, the LoS path acquisition probability can be set to increase as the elevation angle between the UAV (1110) and the base station increases. Here, the elevation angle refers to the angle formed by the connection line between the UAV (1110) and the base station with respect to the horizon. In other words, the higher the UAV (1110) is located, the easier it is to secure a LoS path toward the base station while avoiding other obstacles.

[0158] Ignoring other interference effects, the UAV (1110) has a maximum connection radius of 1110 at a horizontal distance from each base station. In the present disclosure, the maximum connectable radius is the maximum radius within which the UAV (1110) can maintain connectivity with the base station, and is not limited by any special term. For example, the maximum connectable radius may be referred to as the coverage radius of the base station. If the interference effect is taken into account, the UAV (1110) can be connected to the base station if the following [Mathematical Formula 1] is satisfied.

[0159]

[0160] In [Equation 1], is the reduction in the radius of connection possible due to interference, means the total transportation work execution time.

[0161] Additionally, various parameters may be considered to determine the transport path. For example, losses incurred when the UAV (1110) performs a handover between base stations while moving may be considered. When the UAV (1110) performs a handover procedure, there may be a time when the connection with the base station is lost. Furthermore, devices moving at high speeds, such as the UAV (1110), may take longer to complete the handover than devices moving at low speeds. Furthermore, high speeds may increase the probability of handover failure. Therefore, to determine the path of the UAV (1110), the path search decision method needs to be designed to consider losses due to handover.

[0162] Below is the handover cost, which is the loss or cost incurred when performing one handover. , and the handover cost uses the same unit as the transportation work time. That is, the goal for route search in transportation work can be to establish a movement route and handover strategy that minimizes the weighted sum of the time required to perform the transportation work and the number of handovers performed.

[0163] That is, as shown in FIG. 12, the UAV (1210) can move from the starting point to the destination point within the coverage of the base stations (1220#1 to 1220#3). If the UAV leaves the coverage of the base station, the communication connection may be interrupted. In addition, the handover procedure may be performed in the area where the coverage of the first base station (1220#1) and the coverage of the second base station (1220#2) overlap, and handover costs may be incurred. The coverage radius of each base station may be determined by subtracting the amount of reduction due to interference from the maximum connectable radius. That is, the objective function may be set by considering the starting point and the destination point, the speed of the UAV, and maintaining connectivity with the base station. For example, the objective function and constraints as shown in [Table 2] below may be used.

[0164]

[0165] In [Table 2], means the base station number currently connected, Is is an impulse function defined so that it can mean the total number of handovers. The present disclosure proposes a generalized intersection method with hand-off (GIM-HO) technique to solve the optimization problem of mathematical expression 2.

[0166] FIG. 13 illustrates an example of the operation procedure of the GIM-HO technique according to one embodiment of the present disclosure. Referring to FIG. 13, the control center can generate a graph and determine an optimal path to perform the GIM-HO technique.

[0167] Preparation Phase 1: The control center determines whether the path can be navigated. The control center determines whether the UAV is ready to start from the starting point. Arrival point from The control center checks whether a route exists that can be delivered while maintaining connectivity with the base station. If at least one possible route exists, the control center proceeds to the next step. If no route exists, it declares that route search is impossible and terminates the algorithm. For example, if at least one route exists that does not exceed the range of the base station, as in Step 1 of Figure 13, the following steps are performed.

[0168] Phase 2: The control center explores the vertices of the graph. The control center is the starting point. Arrival point , and set the connectable range of each base station, and determine the intersections resulting from the boundaries of the connectable range of each base station as graph vertices. For example, four intersections can be determined as vertices as shown in Fig. 13.

[0169] Step 3: The control center searches for edges in the graph. The control center connects each pair of vertices to form a line segment and then determines whether the line segment falls within the set of reachable ranges of all base stations. The control center can only determine edges within the set of reachable ranges of all base stations as edges in the graph. Therefore, certain line segments that fall within the unreachable range are not considered edges in the graph and are therefore not considered in the pathfinding process. The control center determines the minimum number of handovers and the base station connection order for each edge. The weight of each edge can be determined based on the total time for the UAV to travel along the edge and the minimum number of handovers. For example, as shown in Figure 13, among the lines connecting the four nodes, the starting point, and the destination point, any line segment that falls outside the reachable range of the base station, such as an unreachable line segment, is not included as a graph edge.

[0170] Step 4: The control center searches for an optimal path and a path that can maintain connection to base stations. The control center creates a weighted graph using the graph vertices and edges found in Steps 2 and 3. The control center then uses Dijkstra's algorithm to find the optimal path from the starting point to the destination. The control center searches for an optimal base station connection strategy based on the optimal path and the base station connection order for each edge found in Step 3. For example, as shown in FIG. 13, the UAV can move along the first line segment while maintaining connection to the first base station (1320#2), move along the second line segment while maintaining connection to the second base station, and move along the third line segment while maintaining connection to the third base station.

[0171] The GIM-HO technique proposed in this disclosure may include a procedure for searching for a movement path that maintains connectivity with a ground station through the procedures of the first through fourth preparation stages described above. While the GIM-HO technique uses Dijkstra's algorithm to perform the fourth preparation stage, various methods for searching for an optimal path based on the graph generated in the first through third preparation stages may be implemented.

[0172] The GIM-HO technique differs from the aforementioned intersection technique in the following ways. During graph formation and optimal path search, the GIM-HO technique considers the visit order of all base stations and includes a procedure that considers handover costs. In other words, the GIM-HO technique performs a search procedure to optimize the order in which UAVs visit base stations, thereby finding the optimal path.

[0173] To flexibly utilize the GIM-HO technique according to the UAV's transport tasks and communication conditions, the control center can first perform a preparation phase. That is, through the preparation phase, the control center can obtain the parameters necessary for operating the GIM-HO technique from the external environment. As described above, the parameters for utilizing the GIM-HO technique are defined at the starting point. , arrival point , and the location of each base station , maximum connectable radius , reduction in the connection radius due to interference from each base station , speed of UAV , and handover costs can be included. The method for obtaining each parameter can be implemented as follows.

[0174] - Starting point and arrival point The control center determines the starting and ending points based on the customer's requirements requesting the transport mission. These requirements can be communicated in various ways. For example, the control center can receive customer requirements entered by the user on the UAV via a base station. Alternatively, the control center can receive customer requirements entered from a separate server.

[0175] - Base station location : Base station locations can be obtained in a variety of ways, and are not limited to any specific method. For example, the control center may have a pre-existing delivery map containing base station locations. The control center can receive base station locations from the base station via a backhaul network.

[0176] - Maximum connection radius : The control center determines the maximum reachable radius using the base station's transmission signal strength and the channel model between the UAV and the base station. The control center can receive the transmission signal strength from the base station through the backhaul network. The method for determining the channel model is not limited to a specific method. For example, the control center can determine the channel model based on the LoS path acquisition probability determined based on the elevation angle between the UAV and the base station. The channel model's parameter values ​​can change depending on the building height and density. The control center can use a preset channel model. For example, the control center can have a delivery map that includes the channel model of the mission area along with the base station's location.

[0177] - Reduction in the connectable radius of the mth base station : The control center can determine the amount of reduction in the reachable radius based on the channel environment conditions. The control center can update the amount of reduction in the reachable radius through measurement reports obtained through channel measurements. Therefore, the control center can utilize values ​​measured by various devices included in the transportation environment. In addition, the UAV can perform channel measurements simultaneously while performing the transportation mission and transmit the measurement information to the control center. To this end, the control center can periodically transmit a reference signal to the UAV. The UAV can perform measurements based on the reference signal and transmit a measurement report to the control center. The measurement information can include the SINR index value measured by the UAV. Furthermore, the measurement information can include the location of the UAV along with the measured SINR value. The UAV can measure the location of the UAV in various ways. For example, the location of the UAV can be measured using GPS. The control center and the UAV can be connected through a base station, and the base station can receive information such as the SINR value, the location of the UAV, and the location of the base station from the UAV and transmit the information to the control center through a backhaul network. The control center can determine the reduction in the reachable radius based on at least one of the received UAV's location, SINR value, and the channel model on the base station and delivery map. For example, the control center can determine an SNR index value for the channel between the UAV and the base station, and update the reduction in the reachable radius based on the determined SNR and SINR values.

[0178] - UAV speed : The control center can determine the speed of the UAV. This speed can be determined in various ways and is not limited to a specific method. For example, the control center may determine a maximum critical speed at which the UAV can reach safety. Therefore, if the speed must be reduced due to rain or other reasons, the maximum critical speed may be set lower. In another example, the control center may determine the highest speed value that complies with the legal speed limits of the area where the transport operation is performed. The delivery map maintained by the control center may include legal speed limits for each area.

[0179] Handover costs The handover success rate may vary depending on the UAV's speed. The control center can determine the handover cost based on the handover success rate. The method for determining the handover cost may vary depending on the parameter values ​​that affect the handover success rate or the operator's objectives. For example, the handover cost may consider channel environment indicators and the importance of connectivity for the transport task, and may be determined as shown in [Mathematical Equation 2] below.

[0180]

[0181] In [Equation 2], refers to the speed of the UAV, means the proportion of speed, stands for channel environment indicator, refers to an indicator value for the importance of transportation business connectivity.

[0182] The weighting of speed can adjust the cost of handovers that increases with speed. Therefore, if handovers are sensitive to speed, the weighting of speed can be adjusted. can be set high. For example, Values ​​such as can be used.

[0183] Here, the channel environment index can be set to a higher value in environments where LOS is difficult to secure, such as urban canyons. For example, the channel environment index The city center can be set to 5, the outskirts to 3, and the rural areas to 1.

[0184] The importance of transport business connectivity can be set in various ways. For example, the importance of transport business connectivity can be determined based on the degree of necessity to travel along a given trunk. For example, if channel conditions for a given trunk require measurement, or if using that trunk provides connectivity to other tasks, the importance can be increased to encourage use of that trunk. For example, the importance value of transport business connectivity can be set to a value between 1 and 5. The control center can assign a lower value to the higher importance of transport business connectivity, thereby increasing the likelihood that the trunk will be included in the travel route.

[0185] Referring to the preparatory steps described above, the control center can determine parameter values ​​for using the GIM-HO technique. The GIM-HO technique procedure can be expressed as shown in [Table 3] below.

[0186]

[0187] Referring to [Table 3], the GIM-HO technique can be used to find an optimal route. The GIM-HO technique uses the parameter values ​​determined in the preparation phase as input. Steps 1 through 4 of the GIM-HO technique are then performed. In Step 1, the control center uses the function ChkFea to determine whether a route exists that can be delivered while maintaining connectivity with the base station. A detailed description of the ChkFea function is provided in [Table 4]. In Step 2, the control center establishes the set of vertices of the graph. In Step 3, the control center establishes the set of edges of the graph. The control center must verify that each candidate edge segment is included in the set of reachable ranges of all base stations and search for the order of base station connections within the established edges. The ChkOutHO function can be used to calculate the minimum weight. The ChkOutHO function is described in [Table 5]. In Step 4, the control center uses Dijkstra's algorithm to find the optimal path and the corresponding base station connection strategy. Once Steps 1 through 4 are completed, the control center outputs the optimal UAV path. and base station connection strategy can be obtained.

[0188] Figure 14 illustrates an example of an optimal base station connection strategy corresponding to a given path according to one embodiment of the present disclosure. In Figure 14, the optimal path is an edge I connecting starting points u0 and x1. edge (u0,x1) and x1 and destination point u F Main line connecting I edge (x 1, u f ) is assumed to be included.

[0189] First, the control center establishes the connection order within the base station. The control center is the trunk line I edge(u0,x1) performs connection in the order of the first base station (1420#1) and the second base station (1420#2), and the trunk line I edge (x 1, u f ) may decide to perform connection in the order of the third base station (1420#3) and the fourth base station (1420#4).

[0190] Afterwards, the control center establishes an optimal base station connection strategy. For example, as shown in FIG. 14, the UAV can be set to be connected to the base station with which it is currently communicating for the longest time. For example, the UAV maintains a connection with the first base station (1420#1) until the boundary of the coverage of the first base station (1420#1) to which it is currently connected, and performs a handover to the second base station (1420#2) at the boundary of the coverage of the first base station (1420#1). Afterwards, the UAV maintains a connection with the second base station (1420#2) and performs a handover to the third base station (1420#3) at x1, which is the boundary of the coverage of the second base station. Similarly, at x1, u f On the way to , the UAV maintains a connection with the third base station (1420#3) and performs a handover to the fourth base station (1420#4) at the boundary of the coverage of the third base station (1420#3). Thereafter, the UAV moves to u within the coverage of the fourth base station (1420#4). f can arrive at

[0191] The pseudo code of the function ChkFea can be expressed as shown in [Table 4] below.

[0192]

[0193] The function ChkFea is the starting point Arrival point from It can be used as a function to check whether there is a path that can perform transportation work while maintaining connectivity with the base station. The function ChkFea is the starting point , arrival point , and the location of each base station , maximum connectable radius and reduction in the connection radius due to interference by base station It uses input. Function ChkFea operates based on graph theory. That is, the vertex set of graph G to be used in function ChkFea is determined based on the starting point, the destination point, and the location of each base station. The edge set corresponds to a pair of vertices that can be moved directly without connecting to other base stations. Function ChkFea generates an unweighted graph G with vertex and edge sets. After that, function ChkFea generates an unweighted graph G with the starting point and arrival point It can determine whether or not the graph is connected. The method for determining whether or not it is connected can be implemented in various ways and is not limited to a specific method. For example, the function ChkFea can determine whether or not it is connected using the breadth first search (BFS) algorithm. Here, the BFS algorithm is a search algorithm that first visits adjacent vertices from the starting vertex. The BFS algorithm can search whether or not the vertices of the graph are connected with low complexity. The function ChkFea outputs whether or not the starting point and the destination point are connected. For example, ChkFea means that it is searchable if the starting point and the destination point are connected. can be set as the output value, and if the start point and the destination point are not connected, it means that navigation is not possible. can be set as the output value.

[0194] If the starting and ending points are determined to be connected using the function ChkFea, the function ChkOutHO can be used to calculate the minimum weight for each edge. The function ChkOutHO can be expressed as shown in [Table 5] below.

[0195]

[0196] The input of the function ChkOutHO is two vertices x1, x2 of the line segment to specify the edge candidate, and the arrival point , the location of each base station , maximum connectable radius and reduction in the connection radius due to interference by base station . The ChkOutHO function checks whether the input edge candidate is included in the set of all base stations' reachable ranges, and if the condition is satisfied, it can find the optimal base station visit order and minimum number of handovers corresponding to the edge. The ChkOutHO function uses a safe interval to check whether the edge candidate is included in the set of reachable ranges. The safe interval is a part where connectivity with the base station has been confirmed. The safe interval can be updated by adding additional parts with confirmed connectivity. That is, the ChkOutHO function searches the reachable ranges of base stations with confirmed connectivity from the starting point, and updates the safe interval by adding the confirmed reachable range. For this purpose, the safe interval can be initialized to an initial value. The initial value can be a set that does not include any part, or it can include a confirmed safe interval that is already known. In addition, the ChkOutHO function can be set to minimize the number of base stations that the UAV must connect to in order to move a given line segment, in order to reduce the number of handovers. That is, the number of handovers required for a UAV to maintain connectivity with at least one base station can be set to be minimal. To this end, the base station can be set to be selected so that the longest length can be added to the safety interval when updating the safety interval. The function ChkOutHO indicates that the edge set includes the line segment when the safety interval becomes equal to the input line segment. In the opposite case, the function ChkOutHO indicates that the edge set does not contain the corresponding line segment. Prints out. When outputting, the output of ChkOutHO is the optimal base station visit order of the edge. and the optimal number of handovers may include.

[0197] Therefore, using the above-described method, the optimal base station visit order and minimum number of handovers corresponding to a specific trunk can be found through the function ChkOutHO in the GIM-HO technique.

[0198] The GIM-HO technique can find the optimal transport route and base station connection strategy through the method expressed in [Table 3] above. In addition, the time complexity of the GIM-HO technique is am.

[0199] Figure 15 illustrates an example of a method for a terminal to receive an optimized travel path according to one embodiment of the present disclosure. Referring to Figure 15, the terminal can receive an optimized travel path from the control center and perform transportation tasks, etc.

[0200] In step S1501, the terminal transmits a configuration request signal to the first base station. The configuration request signal may include a message requesting a movement path from the control center. The configuration request signal may also include information required by the control center.

[0201] As described above, during the preparation phase, the control center may require at least one piece of information from the following: the starting point, the destination point, the location of each base station, the maximum reachable radius, the reduction in reachable radius due to interference at each base station, the speed of the terminal, and the handover cost. Therefore, among the above-described pieces of information, information determined by the terminal or known by the terminal may be transmitted to the control center.

[0202] For example, the starting point and destination can be determined by the control center or the terminal. For example, if a user inputs the starting point and destination into the terminal for a transportation task, the configuration request signal may include the starting point and destination.

[0203] As another example, if the control center requires speed information about a terminal, the terminal may transmit the speed information to the first base station. For example, the terminal may determine its moving speed based on at least one of the following factors: the moving environment or the level of cargo being transported. The terminal may transmit a configuration request signal including its speed to the first base station. Additionally, the terminal may transmit speed-related information in a separate message. For example, the terminal may transmit a terminal capability message including its speed to the first base station.

[0204] The first base station, upon receiving the configuration request message, transmits the configuration request message to the control center via the backhaul network. The control center determines the optimal movement path between the starting point and the destination based on the received configuration request message. The optimal movement path can be determined based on the coverage and handover costs of the base stations. To this end, the control center can determine the optimal movement path based on the number of handovers and connectivity with the base stations. For example, the optimal movement path can be determined based on the aforementioned GIM-HO technique. Accordingly, the control center can determine the optimal movement path using the algorithm described above in Tables 3 to 5. For example, the optimal movement path can include at least one edge. In this case, the edge can be generated based on the intersection points of the starting point, the destination, and the boundary of the reachable range. The edge considered for determining the optimal path must be within the reachable range of the base stations. The control center can determine the optimal movement path as the path that minimizes the sum of the weights of the edges connecting the starting point and the destination. The weight of each trunk can be determined based on the product of the time required for a terminal to move along the trunk, the number of handovers, and the handover cost. The handover cost can be determined in the form of [Mathematical Equation 2]. The weight of each trunk can be set so that the number of handovers required for a terminal to maintain connectivity with at least one base station is minimized.

[0205] In step S1503, the terminal receives a configuration response signal from the first base station. The control center transmits information regarding the optimal route determined based on the configuration information signal to the first base station. The first base station transmits the configuration response signal to the terminal to convey the optimal movement route received from the control center. Therefore, the configuration response signal may include information regarding the optimal movement route. If there is no route that can travel from a starting point to a destination while maintaining connectivity with at least one base station, the configuration response signal may include information regarding the impossibility of route search.

[0206] In step S1505, the terminal sets a movement path based on the configuration response signal. The terminal can determine the movement path based on the configuration response signal received from the first base station. If the terminal is a UAV, the terminal's movement path can be set based on information regarding the optimal movement path included in the configuration response signal. If the terminal is a user-controlled vehicle, such as a self-driving car, the terminal can present the user with multiple paths, including the optimal movement path, based on the configuration response signal. The terminal then sets the movement path based on the path selected by the user.

[0207] In step S1507, the terminal receives a reference signal from the second base station. The terminal may receive the reference signal from the second base station for channel estimation.

[0208] In step S1509, the terminal transmits a measurement report to the second base station. The measurement report may include an SINR value measured based on a reference signal and the location of the terminal. The location of the terminal may be measured based on GPS. The second base station transmits the received measurement report to the control center via a backhaul network. The control center may update parameter values ​​for determining a movement path based on the received measurement report. For example, the control center may use the received measurement report to determine a reduction in the reachable radius. can be updated. Therefore, the control center can update the base station connection radius based on the measurement report. If the terminal performs a transport mission, the procedure can be repeated from step S1501. In this case, the control center can determine the terminal's movement path based on the updated parameter values.

[0209] In this case, the control center and the first base station can be operated in an integrated manner. That is, the first base station can perform the functions of the control center, and the first base station can determine the optimal route using the procedures. Therefore, all procedures related to the control center described above can be operated in an integrated manner by the first base station. When the functions of the control center are operated in an integrated manner by the base station, the signaling between the first base station and the control center is omitted, and the signaling between the second base station and the control center can be replaced with the signaling between the second base station and the first base station.

[0210] Figure 16 illustrates an example of a procedure in which a control center transmits a movement path to a terminal according to one embodiment of the present disclosure. Referring to Figure 16, the control center can receive an optimized movement path from the terminal and perform transportation tasks, etc.

[0211] In step S1601, the control center receives a configuration request signal from the terminal. To this end, the first base station may transmit the configuration request signal received from the terminal to the control center. The configuration request signal may include a message requesting a movement route from the control center. The configuration request signal may also include information required by the control center.

[0212] As described above, during the preparation phase, the control center may require at least one piece of information from the following: the starting point, the destination point, the location of each base station, the maximum reachable radius, the reduction in reachable radius due to interference at each base station, the speed of the terminal, and the handover cost. Therefore, among the above-described pieces of information, information determined by the terminal or known by the terminal may be transmitted to the control center.

[0213] For example, the starting point and destination can be determined by the control center or the terminal. For example, if a user determines the starting point and destination on the terminal for a transportation task, the configuration request signal may include the starting point and destination.

[0214] As another example, if the control center requires speed information about a terminal, the terminal can transmit the speed information to the first base station. For example, the terminal can determine its moving speed based on at least one of the following factors: the moving environment or the level of cargo being transported. The terminal can transmit a configuration request signal including its speed to the first base station. However, speed information can be transmitted in a separate message. For example, the terminal can transmit a terminal capability message including its speed to the first base station.

[0215] In step S1603, the control center determines the movement path. Based on the received configuration request message, the control center determines the optimal movement path between the starting point and the destination point. The optimal movement path can be determined based on the coverage of base stations and handover costs. To this end, the control center can determine the optimal movement path based on the number of handovers and connectivity with base stations. For example, the control center can determine the optimal movement path based on the aforementioned GIM-HO technique. If the control center and the first base station are operated in an integrated manner, the first base station can directly determine the optimal path using the GIM-HO technique.

[0216] In step S1605, the control center transmits a configuration response signal to the terminal. The control center transmits information regarding the optimal route determined based on the configuration information signal to the first base station. The first base station transmits the configuration response signal to the terminal to convey the optimal travel route received from the control center. Therefore, the configuration response signal may include information regarding the optimal travel route.

[0217] In step S1607, the control center receives a measurement report from the second base station. Based on the received measurement report, the control center can change parameter values ​​for determining the movement path. For example, the control center can use the received measurement report to determine the amount of reduction in the reachable radius. can be updated. If the terminal performs a new transport mission thereafter, the procedure can be performed again from step S1601. In this case, the control center can determine the terminal's movement path based on the updated parameter values.

[0218] Additionally, if the determined terminal's movement path is configured to be changeable while the terminal is moving, steps S1609 and 1611 may be performed. Specifically, in step S1609, the control center may set new parameter values ​​and modify the existing path based on the measurement report received in step S1607. For example, the control center may set the current terminal's location as the starting location, the arrival location as the transport target point, and search for a new path.

[0219] Figure 17 illustrates an example of signaling for optimizing a terminal's movement path according to one embodiment of the present disclosure. Referring to Figure 17, the first base station (1720#1) and the control center can be operated in an integrated manner. Accordingly, the first base station (1720#1) can determine an optimized movement path and transmit the optimized movement path to the terminal.

[0220] In step S1701, the first terminal (1710) transmits a setup request message to the first base station (1720#1). As described above, the setup request message may include information for the first base station (1720#1) to determine a movement path.

[0221] At step S1703, the first base station (1720#1) sets the terminal's movement path based on the setup request message. For example, the terminal's movement path may be determined using the GIM-HO algorithm.

[0222] In step S1705, the first base station (1720#1) transmits a configuration response message to the first terminal (1710). The configuration response message may include a movement path determined by the first base station (1720#1).

[0223] At step S1707, the first terminal (1710) sets its own travel route based on the received configuration response message. The terminal can set its own travel route to the same route included in the configuration response message. Thereafter, the first terminal (1710) performs transportation tasks, etc., along the corresponding travel route.

[0224] At step S1709, the first terminal (1710) receives a reference signal from the second base station (1720#2). The terminal may be connected to the second base station (1720#2) during transport operations and may perform a segmentation measurement procedure to update channel state information.

[0225] In steps S1711 and S1713, the second base station (1720#2) receives a measurement report from the terminal and transmits the received measurement report to the first base station (1720#1). The first base station (1720#1) can update the parameter values ​​for path setting based on the received measurement report. For example, the first base station (1720#1) can use the received measurement report to determine the amount of reduction in the connectable radius. can be renewed.

[0226] Additionally, if the movement path of the determined first terminal (1710) is set so that the first terminal (1710) can be changed while moving, steps S1715 and S1717 may be performed.

[0227] In steps S1715 and S1717, the first base station (1720#1) updates the movement path using the updated parameters and transmits the updated movement path to the first terminal (1710). In addition, the amount of reduction in the connectable radius may be changed based on the measurement report transmitted by the second terminal to the first base station (1720#1). That is, the second terminal may transmit the measurement report to the first base station (1720#1), and the first base station (1720#1) may update the parameter values ​​for setting the movement path and determine the updated movement path of the first terminal (1710).

[0228] FIG. 18 illustrates signaling for optimizing a movement path and transmitting the optimized path to a first terminal (1810) by a core network (1830) according to one embodiment of the present disclosure. In FIG. 18 , the core network (1830) is not limited to a specific name. Accordingly, the core network (1830) may be referred to as a control center, and may refer to a device that has a function separate from a base station and that determines the movement path of the first terminal (1810).

[0229] In step S1801, the first terminal (1810) transmits a configuration request message to the core network (1830). As described above, the configuration request message may include information for the core network (1830) to determine a movement path. To this end, the first base station (1820#1) may receive the configuration request message from the first terminal (1810) and forward the configuration request message to the core network (1830).

[0230] At step S1803, the core network (1830) sets the terminal's movement path based on the setup request message. For example, the terminal's movement path may be determined using the KIM-HO technique.

[0231] In step S1805, the core network (1830) transmits a configuration response message to the first terminal (1810). The configuration response message may include a movement path determined by the first base station (1820#1). To this end, the first base station (1820#1) may receive the configuration response message from the core network (1830) and transmit the configuration response message to the first terminal (1810).

[0232] At step S1807, the first terminal (1810) sets its own travel route based on the received configuration response message. The terminal can set its own travel route to the same route included in the configuration response message. Thereafter, the first terminal (1810) performs transportation tasks, etc., along the corresponding travel route.

[0233] In step S1809, the first terminal (1810) performs a measurement report procedure. The first terminal (1810) may perform a measurement procedure along a moving route to perform transportation tasks, etc. Accordingly, when the first terminal (1810) is connected to the first base station (1820#1), it may receive a reference signal from the first base station (1820#1) and transmit a measurement report to the first base station (1820#1). When the first terminal (1810) is connected to the second base station (1820#2) while moving, it may receive a reference signal from the second base station (1820#2) and transmit a measurement report to the second base station (1820#2). The first base station (1820#1) and the second base station (1820#2) transmit the measurement reports received from the terminals to the core network (1830). The core network (1830) may update parameter values ​​for path setting based on the received measurement reports. For example, the core network (1830) uses the received measurement report to determine the amount of reduction in the reachable radius. can be renewed.

[0234] Additionally, if the movement path of the determined terminal is set so that the terminal can change while moving, steps S1811 and S1813 may be performed.

[0235] In steps S1811 and S1813, the core network (1830) can update the movement path using the updated parameters and transmit the updated movement path to the first terminal (1810).

[0236] In the procedures described in Figures 11 to 18, the terminal is not limited to a specific device. For example, it can be any device that needs to determine a path to navigate a specific section, not just a UAV. Examples of such devices include autonomous vehicles, drones, and robots. Furthermore, the terminal need not necessarily be unmanned. A user using the terminal can receive multiple paths from the control center and select one of them to set a path. Furthermore, the terminal can transport objects or people through an optimized path.

[0237] The GIM-HO technique proposed in this disclosure can find optimal paths with relatively low time complexity compared to exhaustive search methods. A comparison of the GIM-HO technique with other path finding techniques is shown in Table 6 below.

[0238] Optimal path search technique (*improved by reflecting hand-off) Time complexity Order Performance Maximum difference Exhaustive search (ES) 0ES with fixed association (ES-FA) ES with quantization (ES-Q) intersection technique Proposed GIM-HO technique 0

[0239] In [Table 6], for a fair comparison, other techniques were also improved to consider the handover cost. It can be seen that the GIM-HO technique proposed in this disclosure searches for the optimal path with NP-easy complexity. The ES technique finds the optimal path but is inefficient due to NP-hard complexity. On the other hand, ES-FA, ES-Q, and intersection techniques have NP-easy complexity but have difficulty in finding the optimal path. In the case of ES-FA, ES-Q, and intersection techniques, when the objective function and constraints as in [Table 2] are used, the performance difference with respect to the GIM-HO technique is as follows. The difference in ES-FA and intersection techniques increases with M, and the existing handover cost Unlike when we don't consider There is also a performance difference in the value. Therefore, in environments where handover must be considered, the ES-FA and intersection techniques can be said to have a large performance difference from the proposed GIM-HO technique. In the case of the ES-Q technique, the maximum performance difference is Value-independent and adjustable parameters for path optimization Performance differences occur depending on the value. When using the ES-Q technique, In this case, the performance difference increases with M, resulting in significant performance degradation compared to GIM-HO. On the other hand, In this case, the performance difference decreases with M and eventually converges to 0, but the time complexity order becomes larger than that of the optimal technique, the GIM-HO technique. Therefore, the GIM-HO technique proposed in this disclosure can be seen to be superior to other techniques when comprehensively comparing the time complexity order and the maximum difference in performance.

[0240] That is, the proposed GIM-HO technique can produce the following effects. First, the GIM-HO technique can determine the moving path and secure connectivity with the base station by considering the handover cost between base stations. The GIM-HO technique can find the optimal path with NP-easy complexity for the path finding problem given in [Table 2]. When comprehensively comparing the time complexity order and the difference with the baseline performance, the GIM-HO technique can solve the path finding problem given in [Table 2] more efficiently than other techniques.

[0241] Below, simulation results comparing the performance of the proposed GIM-HO technique with other techniques in a real-world environment are described. To obtain simulation results that reflect a realistic environment, the simulation environment was set as shown in [Table 7].

[0242] Meaning of notation Experimental value Transportation work area 5km × 5km Number of base stations: 15 to 20 Base station antenna height 35m SNR value of reference signal (1m distance, free space) 90dB SINR threshold for base station-UAV connection: 15 dB Maximum connection radius: 754.8 m (subject to change) Reduction in the reachable radius of each base station due to interference [50,500] m (subject to change) UAV's operating speed 20 m / s UAV flight height 100ms Handover cost 5s (subject to change) Channel model related parameters: elevation angle LoS path acquisition probability according to 4.880 0.429 Channel model related parameters: Additional path loss of 0.1 dB depending on whether LoS path is secured 2.1dB

[0243] Figure 19 illustrates an example of simulation results in a real environment according to one embodiment of the present disclosure. Figure 19 shows the results of comparing the GIM-HO technique, the ES technique, the ES-FA technique, the ES-Q technique, and the intersection technique. In Figure 19, the evaluation index means the weighted sum of the mission execution time and the number of handovers. It can be seen that the ES technique with the highest complexity has the lowest evaluation index. The proposed GIM-HO technique also has the same evaluation index as the ES technique. The remaining techniques excluding the ES technique and the GIM-HO technique have relatively higher evaluation indexes, which means that the delivery time increases further. In addition, it can be seen that some of the remaining techniques excluding the ES technique and the GIM-HO technique also increase the number of handovers. In other words, Figure 19 shows the simulation results that the GIM-HO technique can find the same optimal path as the ES technique, and the remaining techniques find different paths from the ES technique.

[0244] In addition, the GIM-HO technique can check whether there is a path that maintains the connectivity of the base station from the starting point to the destination point, as shown in Fig. 20. As shown in Fig. 20, the SINR threshold If the range of possible connections per base station is very high and small, a situation may arise where path finding is impossible, and the GIM-HO technique can detect this.

[0245] Figure 21 illustrates an example of a path search result by handover cost using the GIM-HO technique according to one embodiment of the present disclosure. In Figure 21, the handover cost Simulations were performed by varying the handover cost to 0s, 5s, and 20s. Figure 21 shows that the evaluation index increases as the handover cost increases. Furthermore, as the handover cost increases, the loss due to handover increases, so the route is selected in a way that reduces the number of handovers. As a result, the transport route is determined to reduce the number of handovers even if it travels a longer distance as the handover cost increases.

[0246] It is clear that the examples of the proposed methods described above can also be considered as a type of proposed methods, as they can be included as one of the implementation methods of the present disclosure. Furthermore, the proposed methods described above can be implemented independently, but they can also be implemented in the form of a combination (or merge) of some of the proposed methods. Information regarding the applicability of the proposed methods (or information regarding the rules of the proposed methods) can be defined by a rule such that the base station notifies the terminal of the application of the proposed methods through a predefined signal (e.g., a physical layer signal or a higher layer signal).

[0247] 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 do not explicitly cite each other in the claims may be combined to form embodiments or incorporated into new claims through post-filing amendments.

[0248] Embodiments of the present disclosure can be applied to various wireless access systems. Examples of various wireless access systems include the 3rd Generation Partnership Project (3GPP) or 3GPP2 systems.

[0249] The embodiments of the present disclosure can be applied not only to the various wireless access systems described above, but also to all technical fields that utilize these various wireless access systems. Furthermore, the proposed method can also be applied to mmWave and THz communication systems utilizing ultra-high frequency bands.

[0250] Additionally, embodiments of the present disclosure can be applied to various applications such as autonomous vehicles and drones.

Claims

1. In a method of operating a terminal in a wireless communication system, A step of transmitting a setup request signal to the first base station; A step of receiving a setup response signal based on the setup request signal from the first base station; A step of setting a movement path based on the above setting response signal; A step of receiving a reference signal from a second base station; and Including a step of transmitting a measurement report based on the reference signal to the second base station, The above movement path is determined based on the connection range and handover cost that the terminal can perform communication with each of at least one base station, A terminal operation method in which the above connectable range is updated through the above measurement report.

2. In paragraph 1, The above movement path includes at least one edge, A method of operating a terminal, wherein at least one edge is generated based on the intersection points where a start point, an arrival point, and a boundary of the connectable range intersect.

3. In paragraph 2, The above movement path is determined based on the sum of weights corresponding to at least one edge included in the above movement path, At least one of the above edges is included in the above connectable range, A method of operating a terminal, wherein a weight corresponding to at least one edge is determined based on the product of the time required for the terminal to move along the edge and the number of handovers and the handover cost.

4. In paragraph 3, A method of operating a terminal, wherein the above weight is determined so that the number of handovers required for the terminal to maintain connectivity with at least one base station is minimized.

5. In paragraph 3, A method of operating a terminal, wherein the handover cost is determined based on at least one of a speed of the terminal, a channel environment, and a need to move along at least one trunk line.

6. In paragraph 1, At least one of the above base stations is connected to a control center that remotely controls the terminal through a backhaul network, A method of operating a terminal, wherein the above movement path is determined by the above control center.

7. In paragraph 6, Further comprising the step of receiving an updated movement path from the above control center, The above updated movement path is a terminal operation method determined based on the updated connectable range.

8. In paragraph 7, The above measurement report is a method of operating a terminal, including a SINR (signal to interference plus noise ratio) value measured based on the reference signal and the location of the terminal.

9. In paragraph 8, A method of operating a terminal, wherein the location of the terminal is determined based on the global positioning system (GPS).

10. In paragraph 1, A method of operating a terminal, wherein the above-mentioned setup request signal includes a starting point and an arrival point of the above-mentioned movement path.

11. In Article 10, If there is no path through which the terminal can move from the starting point to the destination point while maintaining connectivity with at least one base station, A method of operating a terminal, wherein the above-mentioned setup response signal includes information regarding the impossibility of route search.

12. In paragraph 1, The above terminal is a method of operating a terminal for transporting objects or people through the above movement path.

13. In a method of operating a first base station in a wireless communication system, A step of receiving a setup request signal from a terminal; A step of determining a movement path based on the above setting request signal; A step of transmitting a setup response signal including information about the movement path to the terminal; A step of receiving a measurement report measured by the terminal from the second base station; and Including a step of updating parameter values ​​for determining the movement path based on the above measurement report, The above movement path is determined based on the connection range and handover cost that the terminal can perform communication with each of at least one base station, A method of operating a base station, wherein the above-mentioned connectable range is updated through the above-mentioned measurement report.

14. In paragraph 13, The step of determining the above movement path is: A step of transmitting the above setup request signal to the control center through a backhaul network; and Further comprising a step of receiving information about the movement path from the control center, A method of operating a base station, wherein the above movement path is determined by the above control center.

15. In paragraph 13, The above movement path includes at least one edge, A method of operating a base station, wherein at least one of the above edges is generated based on the intersections of a starting point, an arrival point, and a boundary of the connectable range.

16. In a wireless communication system, at a terminal, Transmitter and receiver; and comprising a processor connected to the above transceiver, The above processor, Transmit a setup request signal to the first base station, Receive a setup response signal based on the setup request signal from the first base station, Set the movement path based on the above setting response signal, Receive a reference signal from the second base station and Control to transmit a measurement report based on the reference signal to the second base station, The above movement path is determined based on the connection range and handover cost that the terminal can perform communication with each of at least one base station, The above connectable range is updated through the above measurement report, terminal.

17. In a first base station in a wireless communication system, Transmitter and receiver; and comprising a processor connected to the above transceiver, The above processor, Receive a setup request signal from the terminal, Determine the movement path based on the above setup request signal, Transmitting a setup response signal containing information about the movement path to the terminal; Receives a measurement report measured by the terminal from the second base station, and Control to update the parameter values ​​for determining the movement path based on the above measurement report, The above movement path is determined based on the connection range and handover cost that the terminal can perform communication with each of at least one base station, The above connectable range is updated through the above measurement report, the first base station.

18. In communication devices, At least one processor; At least one computer memory coupled to said at least one processor and storing instructions that direct operations when executed by said at least one processor, The above actions are, A step of transmitting a setup request signal to the first base station; A step of receiving a setup response signal based on the setup request signal from the first base station; A step for setting a movement path based on the above setting response signal, A step of receiving a reference signal from a second base station, and Including a step of transmitting a measurement report based on the reference signal to the second base station, The above movement path is determined based on the reachable range and handover cost that the communication device can perform communication for each of at least one base station, A communication device, wherein the above connectable range is updated through the above measurement report.

19. 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: Transmit a setup request signal to the first base station, Receive a setup response signal based on the setup request signal from the first base station, Set the movement path based on the above setting response signal, Receive a reference signal from the second base station and Control to transmit a measurement report based on the reference signal to the second base station, The above movement path is determined based on the reachable range and handover cost that the device can perform communication with respect to at least one base station, A computer-readable medium in which the above connectable range is updated through the above measurement report.

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