WO2022059902A1

WO2022059902A1 - Electronic device supporting wireless communication for automobile, and method performed by electronic device

Info

Publication number: WO2022059902A1
Application number: PCT/KR2021/009395
Authority: WO
Inventors: 주승범; 유승진; 장창원
Original assignee: 삼성전자 주식회사
Priority date: 2020-09-17
Filing date: 2021-07-21
Publication date: 2022-03-24
Also published as: KR20220037279A

Abstract

The present disclosure relates to a method by which an electronic device supports wireless communication for an automobile by using a drone. One aspect of the present disclosure can provide a method performed by an electronic device mounted in an automobile to support wireless communication for the automobile, the method comprising the steps of: allowing communication with a base station by accessing the base station; controlling, on the basis of a determination that a communication state with the base station has deteriorated, the drone by transmitting information related to the location of the drone; and allowing communication between the electronic device and the base station through the drone.

Description

Electronic device supporting wireless communication for automobile and method performed by the electronic device

The present disclosure relates to a method in which an electronic device supports wireless communication for a vehicle using a drone.

The rapid increase in various wireless communication services due to the advent of 5G mobile communication has limitations in satisfying it only by increasing the spectrum efficiency and capacity of the existing sub-6GHz band. In particular, 5G requirements include high data rates (eMMB), very low latency (URLLC), the ability to handle a large number of devices (eMTC), ultra-high reliability and energy efficiency. In order to satisfy these requirements, research on a 5G radio access network (RAN) system to which a new radio access technology based on mmWave is applied is being actively conducted.

The mmWave frequency band is 6 to 100 GHz, and there is a continuous wide bandwidth that can be used compared to the existing band below 6 GHz. Therefore, it may be easy to apply various radio access technologies suitable for service requirements. On the other hand, research on many technical factors that need to be overcome, such as narrow service area due to short radio wave reach, radio wave interference/blocking due to obstacles, mobility support, and reliable data transmission, are needed.

On the other hand, the high-capacity, low-latency communication technology of the 5th generation wireless communication technology is also attracting attention in V2X communication. V2X communication technology refers to a technology in which a vehicle exchanges information with other vehicles, mobile devices, roads, etc. through wired/wireless networks.

V2X is an abbreviation of Vehicle to Everything, and refers to the technology or technology in which a vehicle exchanges information with objects. V2X communication technology is a wireless communication between a vehicle and a network (V2N: Vehicle to Network), a wireless communication between a vehicle and an infrastructure (V2I: Vehicle to Infrastructure), a wireless communication between a vehicle and a vehicle (V2V: Vehicle to Vehicle), a vehicle and It may include wireless communication between pedestrians (V2P: Vehicle to Pedestrian).

In the case of wireless communication using the mmwave frequency band, due to the characteristics of a high-frequency signal, if the Line of Sight (LOS) is not guaranteed, the antenna gain is significantly reduced. Therefore, the maintenance of LOS is an important factor in mmwave implementation.

However, there are many obstacles such as automobiles, pedestrians, and structures on the road, and since the automobile continues to move, there is a problem in that it is difficult for an electronic device mounted on the automobile to support wireless communication to maintain the LOS.

In order to solve this problem, an aspect of the present disclosure provides a method performed by an electronic device mounted on a vehicle to support wireless communication for the vehicle, the method comprising: performing communication with the base station by accessing the base station; controlling the drone by transmitting information related to the location of the drone based on the determination that the communication state with the base station has deteriorated; and performing communication between the electronic device and the base station through the drone.

In addition, in an embodiment of the present disclosure, the controlling of the drone may include: determining that the communication state with the base station has deteriorated based on the strength of a signal received from the base station; and transmitting information related to the location of the drone to the drone based on the determination that the communication state with the base station has deteriorated.

Also, according to an embodiment of the present disclosure, the information related to the location of the drone may include a 3D coordinate value determined according to a predetermined criterion based on the location of the vehicle, the method may be provided.

In an embodiment of the present disclosure, the controlling of the drone may include: determining whether there is a drone available in the vehicle based on a determination that the communication state with the base station has deteriorated; maintaining communication with the base station when there is no drone available; and controlling the drone by transmitting information related to the location of the drone to the drone when there is the available drone.

Also, in an embodiment of the present disclosure, the drone and the electronic device are connected in a D2D communication method, and the electronic device uses the drone as a relay node to communicate with the base station, characterized in that it provides a method can

In an embodiment of the present disclosure, performing communication between the electronic device and the base station through the drone includes: transmitting control information to the drone so that the drone establishes a connection for communication between the base station; performing a discovery process for D2D connection with the drone; establishing a D2D connection with the drone; and transmitting data to the base station through the drone.

In addition, in an embodiment of the present disclosure, receiving a measurement report from the drone; and determining whether to handover based on the measurement report, wherein the measurement report includes: Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Reference Signal-Signal to RS-SINR Interference Noise Ratio), including at least one of, may provide a method.

In addition, based on determining to perform handover in an embodiment of the present disclosure, determining whether to continue using the drone; performing handover through the drone when it is determined to continue using the drone; and when it is determined to use a drone other than the drone, transmitting location-related information to the other drone, and performing communication between other base stations through the other drone. .

Also, in an embodiment of the present disclosure, the electronic device may provide a method, characterized in that the electronic device communicates with at least one of the base station and the drone using a millimeter wave (mmWave).

Another aspect of the present disclosure provides an electronic device mounted on a vehicle to support wireless communication for the vehicle, comprising: a transceiver for transmitting and receiving signals to and from a base station and a drone; a memory for storing programs and data for operation of the electronic device; and by executing the program stored in the memory, accessing the base station to communicate with the base station, and based on the determination that the communication state with the base station has deteriorated, transmit information related to the location of the drone to control the drone and at least one processor configured to perform communication between the electronic device and the base station through the drone.

In addition, in an embodiment of the present disclosure, the at least one processor determines that the communication state with the base station has deteriorated, based on the strength of the signal received from the base station, and determines that the communication state with the base station has deteriorated. Based on the information related to the location of the drone, it is possible to provide an electronic device, characterized in that it transmits to the drone.

In addition, according to an embodiment of the present disclosure, the information related to the location of the drone may provide an electronic device including a three-dimensional coordinate value determined according to a predetermined criterion based on the location of the vehicle.

In addition, in an embodiment of the present disclosure, the at least one processor determines whether there is a drone available in the vehicle based on the determination that the communication state with the base station has deteriorated, and if there is no drone available, It is possible to provide an electronic device, characterized in that it maintains communication with the base station and controls the drone by transmitting information related to the location of the drone to the drone when there is the available drone.

In addition, in an embodiment of the present disclosure, the drone and the electronic device are connected in a D2D communication method, and the electronic device uses the drone as a relay node to communicate with the base station, characterized in that it provides an electronic device can do.

In addition, in an embodiment of the present disclosure, the at least one processor transmits control information to the drone so that the drone establishes a connection for communication between the base stations, and a discovery process for a D2D connection with the drone , establishes a D2D connection with the drone, and transmits data to the base station through the drone.

In addition, in an embodiment of the present disclosure, the at least one processor receives a measurement report from the drone, and determines whether to handover based on the measurement report, and the measurement report includes: Reference Signal Received Power (RSRP); An electronic device including at least one of Reference Signal Received Quality (RSRQ) and Reference Signal-Signal to Interference Noise Ratio (RS-SINR) may be provided.

In addition, in an embodiment of the present disclosure, the at least one processor determines whether to continue using the drone based on determining to perform handover, and when determining whether to continue using the drone, In the case of performing a handover through a handover and determining to use a drone other than the drone, location-related information is transmitted to the other drone, and communication between other base stations is performed through the other drone. device can be provided.

Also, in an embodiment of the present disclosure, the electronic device may provide an electronic device, characterized in that it communicates with at least one of the base station and the drone using a millimeter wave (mmWave).

Another aspect of the present disclosure is to provide one or more computer-readable recording media in which a program mounted on a vehicle to perform a method performed by an electronic device supporting wireless communication for the vehicle is stored, the method comprising: a base station performing communication with the base station by accessing the ; controlling the drone by transmitting information related to the location of the drone based on the determination that the communication state with the base station has deteriorated; and performing communication between the electronic device and the base station through the drone.

1 is a diagram for explaining a beamforming technique.

2 is a view for explaining an automobile environment in which a line of sight (LOS) for wireless communication cannot be maintained.

3 is a schematic diagram of a method in which an electronic device supports wireless communication for a vehicle using a drone according to an embodiment of the present disclosure.

4 illustrates a wireless communication system according to an embodiment of the present disclosure.

5 is a flowchart of a method performed by an electronic device according to an embodiment of the present disclosure.

6 is a detailed flowchart of a method performed by an electronic device according to an embodiment of the present disclosure.

7 is a detailed flowchart of a method performed by a wireless communication system according to an embodiment of the present disclosure.

8 is a signal flow diagram illustrating a wireless communication system for performing communication between an electronic device and a base station through a drone according to an embodiment of the present disclosure.

9A is a block diagram of an electronic device according to an embodiment of the present disclosure.

9B is a detailed block diagram of an electronic device according to an embodiment of the present disclosure.

10A is a block diagram of a drone according to an embodiment of the present disclosure.

10B is a detailed block diagram of a drone according to an embodiment of the present disclosure.

11 is a diagram for explaining an operation performed using artificial intelligence technology in the disclosed embodiment.

12 is a diagram illustrating an antenna device according to a disclosed embodiment that operates in conjunction with a server.

13 is a diagram for describing FIG. 12 in detail.

14 is a diagram illustrating an example of learning and recognizing data by interworking with an electronic device and a server according to an embodiment of the present disclosure;

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art to which the present disclosure pertains can easily implement them. However, the present disclosure may be implemented in several different forms and is not limited to the embodiments described herein. In addition, in order to clearly explain the present disclosure in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Some embodiments of the present disclosure may be represented by functional block configurations and various processing steps. Some or all of these functional blocks may be implemented in various numbers of hardware and/or software configurations that perform specific functions. For example, the functional blocks of the present disclosure may be implemented by one or more microprocessors, or by circuit configurations for a given function. Also, for example, the functional blocks of the present disclosure may be implemented in various programming or scripting languages. The functional blocks may be implemented as an algorithm running on one or more processors. In addition, the present disclosure may employ prior art for electronic configuration, signal processing, and/or data processing, and the like.

In addition, the connecting lines or connecting members between the components shown in the drawings only exemplify functional connections and/or physical or circuit connections. In an actual device, a connection between components may be represented by various functional connections, physical connections, or circuit connections that are replaceable or added.

Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings.

1 is a diagram for explaining a beamforming technique.

Beamforming is a technique of generating a radio wave beam by means of a plurality of antenna elements (or array antenna) to have directivity of radiating and receiving radio waves in a desired specific direction at a desired time from an antenna. For example, the antenna included in the base station may be a smart antenna that controls the phase of the array antenna so that the radio wave radiation direction of the antenna is always the direction in which the terminal is located. In order to maximize the amount of radio waves transmitted and received through the antenna in a desired direction, spatial filtering may be performed.

Beamforming technology implemented using an antenna may require precise phase calibration for each transmission port. This is because, even if the transmit ports of the antenna are manufactured to have the same phase, even if there is an error of only 1 cm in the length of the cable to the transmit port, a large error occurs in beamforming. Therefore, even after the beamforming antenna is installed, a process of compensating for the phase error by periodically checking how much phase error occurs between the antenna ports may be necessary.

As shown in FIG. 1 , the base station 10 according to an embodiment may perform beamforming so that the beam of the antenna is limited to only one terminal. When 5G uses a frequency in a high-frequency band such as a millimeter wave (mmWave) band, the cell coverage becomes much smaller than when using the existing low-frequency band. On the other hand, the wavelength of radio waves is reduced, so that the size of the antenna and the separation distance between the antennas can be reduced, so that many antennas can be arranged at high density in the same area. Therefore, if many antennas are made into a two-dimensional array and beamforming technology is applied, coverage can be expanded and transmission speed can be improved.

On the other hand, the high-capacity low-latency technology using millimeter wave can also be applied to wireless communication technology for automobiles. However, in the case of wireless communication using the millimeter wave frequency band, due to the characteristics of the high frequency signal, if the Line of Sight (LOS) is not guaranteed, the antenna gain is significantly reduced. Therefore, the maintenance of LOS is an important factor in mmwave implementation.

As shown in FIG. 2 , many obstacles such as automobiles, pedestrians, and structures may exist on the road, and since the automobile continues to move, it is difficult for an electronic device mounted on the automobile to support wireless communication to maintain the LOS. has a problem. For example, the vehicle 21 of FIG. 2 cannot maintain the LOS due to the vehicle 22 in front when performing wireless communication with the base station 23 .

Accordingly, the present disclosure proposes a method of supporting wireless communication for a vehicle using a drone in order to solve this problem.

According to an embodiment of the present disclosure, when a situation occurs in which the vehicle 31 cannot maintain the LOS due to an obstacle (eg, the vehicle 32) while carrying at least one drone, the drone 35 may be used as a hot spot to maintain LOS with the base station 33 . The drone 35 according to an embodiment is equipped with a mmWave antenna to serve as a relay node between the vehicle 32 and the base station 33 , thereby helping to increase the coverage of the base station 33 .

As shown in FIG. 4 , in the wireless communication system according to an embodiment, the drone 300 operates as a relay node of the base station 200 between the vehicle-mounted electronic device 100 and the core network 500 . can

Hereinafter, a detailed method of operating the electronic device 100 according to various embodiments will be described with reference to FIGS. 5 to 8 .

The electronic device 100 according to an embodiment may be mounted on a vehicle to support wireless communication for the vehicle. The electronic device 100 according to an embodiment may be a separate device distinct from the vehicle, may be a device included in the vehicle, or may be at least a part of an electronic device that controls the vehicle.

5 is a flowchart of a method of an electronic device according to an embodiment of the present disclosure.

In step S510 , the electronic device 100 according to an embodiment may communicate with the base station 200 by accessing the base station 200 .

The electronic device 100 may attempt to access a network using an antenna of the vehicle as the vehicle in which the electronic device 100 is mounted starts and drives. If the access attempt is successful, the electronic device 100 may perform communication by exchanging data with the base station 200 .

In step S520 , the electronic device 100 according to an embodiment transmits information related to the location of the drone 300 to the drone 300 based on the determination that the communication state with the base station 200 has deteriorated. 300) can be controlled.

The electronic device 100 according to an embodiment may determine that the communication state with the base station 200 has deteriorated based on the strength of the signal received from the base station 200 . For example, the electronic device 100 has a predetermined gain measurement index of at least one of Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Reference Signal-Signal to Interference Noise Ratio (RS-SINR). When the value is less than the value, it can be determined that the communication state with the base station 200 has deteriorated.

When it is difficult to maintain the LOS with the base station 200 , the electronic device 100 may determine that the communication state has deteriorated and consider switching to a communication method using a drone.

The electronic device 100 according to an embodiment may determine whether there is a drone 300 usable in the vehicle based on the determination that the communication state with the base station 200 has deteriorated. When there is no drone 300 available, the electronic device 100 may continue to maintain communication with the base station 200 . When there is an available drone 300 , the electronic device 100 may control the drone 300 by transmitting information related to the location of the drone 300 to the drone 300 .

The electronic device 100 may transmit information related to the location of the drone 300 to the drone 300 based on the determination that the communication state with the base station 200 has deteriorated. For example, the information related to the location of the drone 300 may include a 3D coordinate value determined according to a predetermined criterion based on the location of the vehicle.

The electronic device 100 may determine a position of the drone relative to the vehicle in which the signal gain is measured to be high, and control the drone to move to the determined position.

In step S530 , the electronic device 100 according to an embodiment may perform communication between the electronic device 100 and the base station 200 through the drone 300 .

The electronic device 100 according to an embodiment may use a millimeter wave (mmWave) when performing communication with at least one of the base station 200 and the drone 300 .

The drone 300 and the electronic device 100 are connected in a D2D communication method, and the electronic device 100 may communicate with the base station 200 using the drone 300 as a relay node. D2D communication refers to a method in which geographically close electronic devices communicate directly without going through an infrastructure such as a base station.

The electronic device 100 establishes a connection for the drone 300 to communicate with the base station 200 in order to perform communication between the electronic device 100 and the base station 200 through the drone 300 . to transmit control information to the drone 300 . When the drone 300 establishes a connection with the base station 200 , the electronic device 100 may perform a discovery process for a D2D connection with the drone 300 . When the discovery process with the drone 300 is completed, the electronic device 100 may establish a D2D connection with the drone 300 . The electronic device 100 may transmit data to the drone 300 through the D2D connection, and the drone 300 may transmit the corresponding data to the base station 200 .

Meanwhile, as the vehicle in which the electronic device 100 is mounted moves, the drone 300 also moves, and the drone 300 may move out of an area in which the base station 200 is being serviced and move to a service area of a neighboring base station. As the drone 300 leaves the service area of the base station 200 , if the signal strength and communication quality transmitted and received by the drone 300 deteriorate, handover to a neighboring base station may be required.

In relaying communication between the electronic device 100 and the base station 200 , the drone 300 according to an embodiment transmits a measurement report indicating a communication state to the electronic device 100 when signal strength and communication quality are not good. ) can be sent to

The electronic device 100 may receive a measurement report from the drone 300 . The electronic device 100 may determine whether to handover based on the measurement report. For example, the measurement report may include at least one value of RSRP, RSRQ, and RS-SINR. When the value included in the measurement report is equal to or less than a threshold value, the electronic device 100 may determine that handover is necessary.

The electronic device 100 may determine whether to continue using the drone 300 based on the determination to perform the handover. The electronic device 100 may perform handover through the drone 300 when it is determined to continue using the drone 300 in use. However, when the electronic device 100 determines to use another drone by replacing the drone 300 in use, the electronic device 100 transmits location-related information to the other drone, and a hand for communication with another base station through the other drone. Over can be done.

For example, the electronic device 100 may compare RSRP of a home cell currently being serviced with RSRP of a neighbor cell. When the RSRP of the neighboring cell is higher than the RSRP of the home cell by more than a threshold level, the electronic device 100 may determine that handover is possible by continuing to use the drone 300 in use. However, if a neighbor cell capable of handover using the drone 300 (ie, a neighbor cell having an RSRP greater than or equal to a threshold level than the RSRP of the home cell) is not found, the electronic device 100 performs handover using another drone. can decide to do In this case, in order to perform handover using another drone, the electronic device 100 may launch another drone in the vehicle or search for another drone in the vicinity.

6 is a detailed flowchart of a method of an electronic device according to an embodiment of the present disclosure.

In step S610 , the electronic device 100 according to an embodiment may communicate with the base station 200 by accessing the base station 200 .

In step S620 , the electronic device 100 according to an embodiment may periodically check a communication state with the base station 200 . As the vehicle in which the electronic device 100 is mounted moves, if a line of sight (LOS) between the electronic device 100 and the base station 200 is not secured, a gain for a signal transmitted and received from the electronic device 100 . The measurement index value will decrease. The electronic device 100 may determine that the communication state with the base station 200 has deteriorated when the gain measurement index value for the transmitted/received signal is equal to or less than a threshold value.

In step S630 , the electronic device 100 according to an embodiment may determine whether there are available drones in or around the vehicle based on the determination that the communication state with the base station 200 has deteriorated.

When there are no drones available in or around the vehicle, the electronic device 100 may continue to maintain communication with the base station 200 . Alternatively, when there is no drone available, the electronic device 100 may fallback to 4G wireless communication or 3G wireless communication to maintain communication with the base station 200 .

Meanwhile, when there is an available drone 300 , in step S640 , the electronic device 100 may control the drone 300 to establish a connection between the drone 300 and the base station 200 . The electronic device 100 may control the drone 300 to move the drone 300 to an optimal position, and may perform communication between the electronic device 100 and the base station 200 through the drone 300 .

The electronic device 100 determines the position of the drone 300 according to a predetermined criterion based on the position of the vehicle in which the electronic device 100 is mounted, and provides the three-dimensional coordinate value of the determined position to the drone 300 . By transmitting, it is possible to control the drone 300 to move to the determined position. In this case, if an obstacle is found while the drone 300 is flying to the determined location, the electronic device 100 may determine a different location and control the drone 300 to move to another location.

In step S650 , the electronic device 100 according to an embodiment may establish a D2D connection with the drone 300 . In step S660 , the electronic device 100 may communicate with the base station 200 through the drone 300 .

7 is a detailed flowchart of a method of a wireless communication system according to an embodiment of the present disclosure.

After the vehicle is turned on in step S701, the electronic device 100 mounted in the vehicle may attempt to access the network using the vehicle's antenna without the aid of a drone. If the access attempt is successful, in step S703 , the electronic device 100 may communicate with the base station 200 .

In operation S705, the electronic device 100 may determine whether NLOS (Non-Line of Sight) is present. When the electronic device 100 and the base station 200 perform mmWave-based wireless communication, when the LOS (Line of Sight) between the electronic device 100 and the base station 200 is not secured as the vehicle moves, RSRP, etc. may decrease the value of the gain metric. When the gain measurement index value is equal to or less than the threshold value, the electronic device 100 may determine that it is an NLOS situation.

In step S709 , the electronic device 100 may check whether there is a drone currently available in the vehicle. If there is no drone available, in step S707 , the electronic device 100 may perform a handover in an existing manner or may fallback to 4G wireless communication or 3G wireless communication to continue communication.

However, when there is an available drone, in step S711 , the electronic device 100 may control the drone 300 to perform an attach process between the drone 300 and the base station 200 .

The electronic device 100 may control the drone 300 to move to a predetermined location for communication. The position to which the drone 300 moves may be a predetermined position by performing a simulation related to mmWave communication between the vehicle antenna and the drone. An artificial intelligence model may be used to determine a location to which the drone 300 will move.

According to an embodiment, when a drone moves along a virtual semicircle or a virtual hemispherical surface having a radius of a predetermined distance from the vehicle during vehicle development, gain values of a communication signal that vary depending on the positions of the drone are measured. simulation can be performed. For example, a drone measures a signal gain while moving to a plurality of candidate positions determined at intervals of a predetermined angle (eg 15 degrees, 30 degrees 45 degrees, etc.) along an imaginary semicircle with a radius of 5 m centered on the vehicle. can do. The artificial intelligence model for determining the moving position of the drone may learn each candidate position of the drone and a gain measured at the candidate position. Priority may be assigned to candidate positions in an order of increasing gain.

Candidate positions may be expressed as relative coordinate values with respect to the vehicle. The drone 300 may fly toward a predetermined location selected from among candidate locations based on the learned relative coordinate values. For example, the electronic device 100 may select a location to which the drone 300 will move from among the candidate locations according to the priority assigned to the candidate locations. The electronic device 100 may select a candidate position having the highest gain measured during simulation from among a plurality of candidate positions. Alternatively, the electronic device 100 may select a location to which the drone 300 will move based on the output value of the pre-learned artificial intelligence model.

The drone 300 may move to another candidate position when an obstacle is found while flying based on the relative coordinates for the predetermined position. The drone 300 may access the network by performing a general access procedure with the base station 200 using mmWave. For example, the electronic device 100 may control the drone 300 to move to a candidate location having the highest priority, and if an obstacle is found, the electronic device 100 may control the drone 300 to move to a candidate location of the next priority. there is.

In step S713 , the drone 300 may perform D2D communication with the electronic device 100 mounted in the vehicle.

When the connection between the drone 300 and the electronic device 100 is completed in step S715 and the drone 300 is notified that the drone 300 is in a relay role, the electronic device 100, the drone 300 and the network (eg For example, communication between the base stations 200 may be completed. Hereinafter, a communication connection procedure between the electronic device 100 - the drone 300 - the base station 200 will be described in detail with reference to FIG. 8 .

First, in step S801 , the electronic device 100 may transmit a message requesting to start a connection procedure between the drone 300 and the base station 200 to the drone 300 .

In step S803, the drone 300 and the base station 200 may perform a radio resource control (RRC) connection establishment procedure. In the RRC connection establishment procedure, the drone 300 requests an RRC setup from the base station 200 , receiving an RRC setup response message from the base station 200 , and the drone 300 asks the base station 200 for RRC setup It may include sending a completion message.

In step S805 , the drone 300 may transmit sidelink UE information to the base station 200 . The sidelink terminal information is a message used to inform the base station 200 of information on the sidelink between the electronic device 100 and the drone 300 . The drone 300 may be allocated a transmission resource from the base station 200 based on the sidelink terminal information.

In step S807 , the base station 200 may transmit an RRC connection reconfiguration message to the drone 300 . In step S809 , the drone 300 may transmit an RRC connection reconfiguration complete message to the base station 200 .

When the RRC connection re-establishment is completed, in step S811 , the electronic device 100 may transmit a D2D discovery solicitation to the drone 300 . In step S813 , the drone 300 may transmit a D2D discovery response to the electronic device 100 . When the discovery is completed, the electronic device 100 may transmit a D2D communication request in step S815. When the D2D communication acceptance message is received from the drone 300 in step S817, the electronic device 100 may transmit data in step S819.

In step S821 , the drone 300 may transmit data and network information to the base station 200 .

Returning to the description of FIG. 7 , in step S717 , the drone 300 may transmit a measurement report to the electronic device 100 when the strength and quality of a transmitted or received signal is not good. In step S719 , the electronic device 100 may determine whether a handover is necessary based on the measurement report received from the drone 300 .

When it is determined that handover is necessary, in step S721 , the electronic device 100 may determine whether it is possible to perform handover to another cell using the currently used drone 300 . When handover using the currently used drone 300 is possible, in step S723 , the electronic device 100 performs handover using the drone 300 and communicates with another base station through the drone 300 . can do.

If handover using the currently used drone 300 is not possible, in step S725, the electronic device 100 may determine whether there are additionally available drones in or around the vehicle. For example, when there is an additional drone additionally available in the vehicle, the electronic device 100 may launch the additional drone to communicate with the base station 200 through the drone. For the additional drone, steps S711 to S715 are performed again, so that a connection between the electronic device 100 , the additional drone, and the base station 200 may be established.

If there is no additional drone available in or around the vehicle, in step S707, the electronic device 100 performs handover in the conventional manner, or falls back to 4G wireless communication or 3G wireless communication. Communication can continue.

As described above, according to various embodiments of the present disclosure, the problem that the LOS cannot be maintained due to many obstacles between the electronic device and the base station can be solved using a drone. In addition, according to various embodiments of the present disclosure, there is an advantage in that a range in which mmWave can be used is widened and network performance of a vehicle can be improved. Hereinafter, specific configurations of the electronic device 100 and the drone 300 will be described.

The configuration illustrated in FIG. 9A may be understood as a configuration of the electronic device 100 . In the present disclosure, the electronic device 100 may refer to an electronic device mounted on, connected to, included in, or controlling a vehicle.

The electronic device 100 illustrated in FIG. 9A may perform methods according to various embodiments of the present disclosure, and the descriptions of FIGS. 3 to 8 may be applied. Therefore, the content overlapping with the above will be omitted.

Referring to FIG. 9A , the electronic device 100 includes a communication unit 110 , a memory 120 , and a processor 130 .

The communication unit 110 performs functions for transmitting and receiving signals through a wireless channel. For example, the communication unit 110 performs a function of converting between a baseband signal and a bit stream according to a physical layer standard of the system. For example, when transmitting data, the communication unit 110 generates complex symbols by encoding and modulating the transmitted bit stream. In addition, when data is received, the communication unit 110 restores the received bit stream by demodulating and decoding the baseband signal.

In addition, the communication unit 110 up-converts the baseband signal into an RF band signal, transmits the signal through the antenna, and down-converts the RF band signal received through the antenna into a baseband signal. For example, the communication unit 110 may include a transmit filter, a receive filter, an amplifier, a mixer, an oscillator, a digital to analog converter (DAC), an analog to digital converter (ADC), and the like.

Also, the communication unit 110 may include a plurality of transmission/reception paths. Furthermore, the communication unit 110 may include at least one antenna array including a plurality of antenna elements. The communication unit 110 may use a millimeter wave (mmWave) when performing communication with at least one of the base station 200 and the drone 300 .

In terms of hardware, the communication unit 110 may include a digital unit and an analog unit (eg, a radio frequency integrated circuit (RFIC)). Here, the digital circuit and the analog circuit may be implemented as one package. Also, the communication unit 110 may include a plurality of RF chains. Furthermore, the communication unit 110 may perform beamforming.

The communication unit 110 transmits and receives signals as described above. Accordingly, all or part of the communication unit 110 may be referred to as a 'transmitter', a 'receiver', or a 'transceiver'. In addition, in the following description, transmission and reception performed through a wireless channel are used to mean that the above-described processing is performed by the communication unit 110 .

The memory 20 stores data such as a basic program, an application program, and setting information for the operation of the electronic device 100 . The memory 120 may be configured as a volatile memory, a non-volatile memory, or a combination of a volatile memory and a non-volatile memory. In addition, the memory 120 provides stored data according to the request of the processor 130 .

The processor 130 controls overall operations of the electronic device 100 . For example, the processor 130 transmits and receives a signal through the communication unit 110 . In addition, the processor 130 writes data to and reads data from the memory 120 . In addition, the processor 130 may perform the functions of the protocol stack required by the communication standard. To this end, the processor 130 may include at least one processor or microprocessor, or may be a part of the microprocessor. Also, a part of the communication unit 110 and the processor 230 may be referred to as a communication processor (CP). According to embodiments, the processor 130 may control the electronic device 100 to perform operations according to embodiments to be described later.

Although the electronic device 100 is illustrated as including one processor in FIG. 9A , the embodiment is not limited thereto, and the electronic device 100 may include a plurality of processors. At least some of the operations and functions of the processor 130 described below may be performed by a plurality of processors.

The processor 130 according to an embodiment may control the communication unit 110 to communicate with the base station 200 by accessing the base station 200 .

The processor 130 may attempt to access the network using an antenna of the vehicle. If the access attempt is successful, the processor 130 may control the communication unit 110 to perform communication by exchanging data with the base station 200 .

The processor 130 according to an embodiment may determine to continue communication with the base station 200 using the drone 300 based on the determination that the communication state with the base station 200 has deteriorated. The processor 130 may control the drone 300 by transmitting information related to the location of the drone 300 to the drone 300 . The processor 130 may determine that the communication state with the base station 200 has deteriorated based on the strength of the signal received from the base station 200 . For example, when the gain measurement index of at least one of RSRP, RSRQ, and RS-SINR is less than or equal to a predetermined value, the processor 130 may determine that the communication state with the base station 200 has deteriorated.

The processor 130 according to an embodiment may determine whether there is a drone 300 usable in the vehicle based on the determination that the communication state with the base station 200 has deteriorated. When there is no drone 300 available, the processor 130 may control the communication unit 110 to continuously maintain communication with the base station 200 . For example, the processor 130 may control the communication unit 110 to maintain communication with the base station 200 by falling back to 4G wireless communication or 3G wireless communication when there is no drone available. there is. When there is an available drone 300, the processor 130 transmits information related to the location of the drone 300 to the drone 300 to control the drone 300 to move to a location suitable for communication. .

The processor 130 may transmit information related to the location of the drone 300 to the drone 300 based on the determination that the communication state with the base station 200 has deteriorated. For example, the information related to the location of the drone 300 may include a 3D coordinate value determined according to a predetermined criterion based on the location of the vehicle.

The processor 130 according to an embodiment may control the communication unit 110 to perform communication between the electronic device 100 and the base station 200 through the drone 300 . The drone 300 and the electronic device 100 are connected in a D2D communication method, and the electronic device 100 may communicate with the base station 200 using the drone 300 as a relay node.

The processor 130 according to an embodiment establishes a connection for communication between the drone 300 and the base station 200 in order to perform communication between the electronic device 100 and the base station 200 through the drone 300 . Control information may be transmitted to the drone 300 to establish. When the drone 300 establishes a connection with the base station 200 , the processor 130 may perform a discovery process for a D2D connection with the drone 300 . When the discovery process with the drone 300 is completed, the processor 130 may establish a D2D connection with the drone 300 . The processor 130 may transmit data to the drone 300 through the D2D connection, and transmit the corresponding data to the base station 200 through the drone 300 .

Meanwhile, as the vehicle in which the electronic device 100 is mounted moves, the drone 300 also moves along with it, and the drone 300 may move out of an area in which the base station 200 is being serviced and move to a service area of a neighboring base station. As the drone 300 leaves the service area of the base station 200 , if the strength and communication quality of a transmitted/received signal deteriorates, a handover to a neighboring base station may be required.

In relaying communication between the electronic device 100 and the base station 200 , the drone 300 according to an embodiment transmits such a measurement report to the electronic device 100 when signal strength and communication quality are not good. can

The processor 130 may receive a measurement report from the drone 300 through the communication unit 110 . The processor 130 may determine whether to handover based on the measurement report. The processor 130 may determine that handover is necessary when a value included in the measurement report, such as RSRP, is less than or equal to a threshold value.

The processor 130 may determine whether to continue using the drone 300 based on the determination to perform the handover. The processor 130 may perform handover through the drone 300 when it is determined to continue using the drone 300 in use. However, when the processor 130 determines to use another drone to replace the drone 300 in use, the processor 130 transmits location-related information to the other drone, and a handover for communication with another base station through the other drone can be performed.

Meanwhile, not all of the components illustrated in FIG. 9A are essential components of the electronic device 100 . The electronic device 100 may be implemented by more components than those illustrated in FIG. 9A . For example, as shown in FIG. 9B , the electronic device 100 according to some embodiments includes an input unit 950 , a sensing unit 940 , an A/V input unit 970 , and an output unit 960 . It may further include at least one.

The electronic device 100 illustrated in FIG. 9B may perform all of the operations and functions of the electronic device 100 described with reference to FIGS. 3 to 8 . Accordingly, components of the electronic device 100 that have not been described so far will be described below.

The input unit 950 means a means for a user to input data for controlling the electronic device 100 . For example, the user input unit 950 includes a key pad, a dome switch, and a touch pad (contact capacitive method, pressure resistance film method, infrared sensing method, surface ultrasonic conduction method, integral type). There may be a tension measurement method, a piezo effect method, etc.), a jog wheel, a jog switch, and the like, but is not limited thereto. The input unit 950 may receive a user input necessary to support wireless communication of the vehicle.

The output unit 960 may output an audio signal, a video signal, or a vibration signal, and the output unit 960 may include a display unit, a sound output unit, and a vibration motor.

The sensing unit 940 may detect a state of the electronic device 100 or a state around the electronic device 100 , and transmit the sensed information to the processor 130 .

The sensing unit 940 may include a magnetic sensor, an acceleration sensor, a temperature/humidity sensor, an infrared sensor, a gyroscope sensor, a location sensor (eg, GPS), a barometric pressure sensor, a proximity sensor, and an RGB sensor. (illuminance sensor) may include, but is not limited thereto.

The A/V (Audio/Video) input unit 970 is for inputting an audio signal or a video signal, and may include a camera and a microphone.

As shown in FIG. 9B , the communication unit 110 of the electronic device 100 according to an embodiment of the present disclosure emits and receives radio waves from the antenna unit 914 in a desired direction at a desired time (ie, a beam). It may include a phase control unit 911 (for performing forming). The communication unit 110 may include a transceiver 913 for radiating and receiving phase-controlled radio waves through the antenna unit 914 .

The configuration shown in FIG. 10A may be understood as a configuration of the drone 300 . In the present disclosure, the drone 300 may mean the entire unmanned aerial vehicle including the electronic control device, but is not limited thereto. In the present disclosure, the drone 300 may refer to a separate electronic device distinguished from the flight driving unit main body including a propeller for flight, a sensor module for sensing an attitude or state, and a battery for supplying power. The drone 300 may refer to an electronic device mounted on a drone, connected to the drone, included in the drone, or controlling the drone. For example, the drone 300 may refer to a drone control system, a communication terminal mounted on the drone, or a drone communication system.

The drone 300 illustrated in FIG. 10A may perform the method of the drone 300 according to various embodiments of the present disclosure, and the descriptions of FIGS. 3 to 8 may be applied. Accordingly, the content overlapping with the above will be omitted.

Referring to FIG. 10A , the drone 300 may include a communication unit 310 , a memory 320 , and a processor 330 .

The communication unit 310 performs functions for transmitting and receiving signals through a wireless channel. For example, the communication unit 310 performs a function of converting between a baseband signal and a bit stream according to a physical layer standard of the system. For example, when transmitting data, the communication unit 310 generates complex symbols by encoding and modulating the transmitted bit stream. In addition, when receiving data, the communication unit 310 restores the received bit stream by demodulating and decoding the baseband signal.

In addition, the communication unit 310 up-converts the baseband signal into an RF band signal, transmits the signal through the antenna, and down-converts the RF band signal received through the antenna into a baseband signal. For example, the communication unit 310 may include a transmit filter, a receive filter, an amplifier, a mixer, an oscillator, a digital to analog converter (DAC), an analog to digital converter (ADC), and the like.

Also, the communication unit 310 may include a plurality of transmission/reception paths. Furthermore, the communication unit 310 may include at least one antenna array including a plurality of antenna elements.

In terms of hardware, the communication unit 310 may include a digital unit and an analog unit (eg, a radio frequency integrated circuit (RFIC)). Here, the digital circuit and the analog circuit may be implemented as one package. Also, the communication unit 310 may include a plurality of RF chains. Furthermore, the communication unit 310 may perform beamforming.

The communication unit 310 transmits and receives signals as described above. Accordingly, all or part of the communication unit 310 may be referred to as a 'transmitter', a 'receiver', or a 'transceiver'. In addition, in the following description, transmission and reception performed through a wireless channel are used in the meaning of including processing as described above by the communication unit 310 .

The memory 320 stores data such as a basic program, an application program, and setting information for the operation of the drone 300 . The memory 320 may be configured as a volatile memory, a non-volatile memory, or a combination of a volatile memory and a non-volatile memory. In addition, the memory 320 provides stored data according to the request of the processor 330 .

The processor 330 controls overall operations of the drone 300 . For example, the processor 330 transmits and receives a signal through the communication unit 310 . In addition, the processor 330 writes data to and reads data from the memory 320 . In addition, the processor 330 may perform the functions of the protocol stack required by the communication standard. To this end, the processor 330 may include at least one processor or microprocessor, or may be a part of the microprocessor. Also, a part of the communication unit 310 and the processor 330 may be referred to as a communication processor (CP). According to embodiments, the processor 330 may control the drone 300 to perform operations according to embodiments to be described later.

Although the drone 300 is illustrated as including one processor in FIG. 10A , the embodiment is not limited thereto, and the drone 300 may include a plurality of processors. At least some of the operations and functions of the processor 330 described below may be performed by a plurality of processors.

The processor 330 according to an embodiment may receive control information related to the initial position of the drone 300 and information related to the electronic device 100 and/or the base station from the electronic device 100 .

The processor 330 according to an embodiment may move based on control information related to an initial location to support communication between the electronic device 100 and the base station 200 . For example, the control information related to the initial location may include a 3D coordinate value of a location where the drone 300 is to be placed.

The processor 330 according to an embodiment may access the network by performing a general access procedure with the base station 200 using mmWave. The processor 330 may control the communication unit 310 to perform D2D communication with the electronic device 100 mounted in the vehicle.

When the connection between the drone 300 and the electronic device 100 is completed, the drone 300 performs a relay role, so that the communication connection between the electronic device 100 - the drone 300 - the base station 200 can be completed. .

On the other hand, the processor 330 according to an embodiment, as the drone 300 leaves the service area of the base station 200, when the strength and communication quality of a transmitted and received signal deteriorates, a measurement report related to communication quality is provided. may be transmitted to the electronic device 100 . In response to the measurement report transmitted to the electronic device 100 , the processor 330 may perform handover to another base station.

Meanwhile, not all of the components shown in FIG. 10A are essential components of the drone 300 . The drone 300 may be implemented by more components than those shown in FIG. 10A . For example, as shown in FIG. 10B , the drone 300 according to some embodiments includes an input unit 1050 , a sensing unit 1040 , an A/V input unit 370 , an output unit 360 , and a driving unit. At least one of (1080) may be further included.

The drone 300 shown in FIG. 10B may perform all of the operations and functions of the drone 300 described with reference to FIGS. 3 to 8 . Accordingly, the components of the drone 300 that have not been described so far will be described below.

The input unit 1050 means a means for a user to input data for controlling the drone 300 . The output unit 360 may output an audio signal, a video signal, or a vibration signal, and the output unit 360 may include a display unit, a sound output unit, and a vibration motor.

The sensing unit 1040 may detect the posture, state, or surrounding state of the drone 300 , and transmit the sensed information to the processor 330 . The sensing unit 1040 may include a magnetic sensor, an acceleration sensor, a temperature/humidity sensor, an infrared sensor, a gyroscope sensor, a location sensor (eg, GPS), a barometric pressure sensor, a proximity sensor, and an RGB sensor. (illuminance sensor) may include, but is not limited thereto.

The A/V (Audio/Video) input unit 370 is for inputting an audio signal or a video signal, and may include a camera and a microphone.

The driving unit 1080 may include a propeller for flight, a motor, and a battery for supplying power.

As shown in FIG. 10B , the communication unit 310 of the drone 300 according to an embodiment of the present disclosure transmits and receives radio waves from the

antenna units

1014 and 1018 in a desired direction at a desired time (that is, and phase controllers 1011 and 1015 (for performing beamforming). The communication unit 310 may include

transceivers

1013 and 1017 for radiating and receiving phase-controlled radio waves through the

antenna units

1014 and 1018 .

As shown in FIG. 9B , according to an embodiment, the electronic device 100 includes only one antenna module supporting mmWave, and one selected from the drone 300 or the base station 200 using one antenna module. can communicate

On the other hand, as shown in FIG. 10B , according to an embodiment of the present disclosure, the drone 300 may include two or more antenna modules. As shown in FIG. 10B , the drone 300 performing the relay role according to an embodiment performs D2D communication with the drone-base station antenna unit 1014 and the electronic device 100 to communicate with the base station 200 . Two or more antenna modules including the drone-device antenna unit 1018 may be required.

If the drone performs a relay role using a low frequency band, only one antenna module may perform a relay role. However, since the drone 300 according to an embodiment of the present disclosure uses the mmWave communication method, two or more antenna modules are required. Accordingly, the drone 300 according to an embodiment of the present disclosure may use two or more antenna modules preset so that directivity between devices corresponds to each other. For example, the drone 300 uses a first antenna module preset to have a high gain according to the communication situation between the vehicle and the antenna of the drone 300 for communication with the vehicle, and the base station 200 and the drone 300 ) may be used for communication with the base station 200 using a second antenna module preset to have a high gain according to the communication situation between the antennas. That is, the drone 300 according to an embodiment of the present disclosure has the advantage of being able to obtain a higher gain compared to the case of using the existing legacy technology by using two or more antenna modules preset to correspond to directivity between devices.

Meanwhile, according to an embodiment of the present disclosure, the drone 300 may be controlled to move along with the movement of the vehicle, and may be disposed in an optimal position to maintain high communication quality. In this case, in determining the position of the drone 300 , artificial intelligence (AI) may be used. However, the present disclosure is not limited to an embodiment using artificial intelligence in determining the location of the drone 300 . In various embodiments, at least one operation among operations performed by at least one of the electronic device 100 and the drone 300 may be performed using artificial intelligence technology. For example, artificial intelligence may be used in a process in which the electronic device 100 determines whether to perform NLOS or whether to perform handover.

Hereinafter, operations performed using artificial intelligence technology according to various embodiments of the present disclosure will be described with reference to FIGS. 11 to 13 .

An artificial intelligence system is a computer system that implements human-level intelligence, and unlike the existing rule-based smart system, it is a system in which a machine learns, judges, and becomes smarter by itself. As artificial intelligence systems are used, the recognition rate improves and users can understand user preferences more accurately.

Artificial intelligence technology consists of machine learning (eg, deep learning) and elemental technologies using machine learning. Machine learning is an algorithm technology that categorizes/learns characteristics of input data by itself, and element technology is a technology that uses machine learning algorithms such as deep learning, such as language understanding, visual understanding, reasoning/prediction, knowledge expression, motion control, etc It consists of the technical fields of

Specifically, at least one of i) determining whether NLOS is performed in the processor 130, ii) determining the location of the drone, and iii) determining whether to perform handover, It may be performed using artificial intelligence technology that performs calculations through a neural network. Specifically, the above-described ii) 'operation of determining the position of the drone' refers to 'the position of the drone and the drone for the position of the vehicle according to a criterion learned in advance based on the measured value of the signal gain from the drone at the position. It can be an operation to determine the relative position of

Artificial intelligence technology (hereinafter, 'AI technology') is a technology that performs calculations through a neural network and processes input data such as analysis and/or classification to obtain a desired result.

Such AI technology can be implemented using algorithms. Here, an algorithm or a set of algorithms for implementing AI technology is called a neural network. The neural network may receive input data, perform the above-described operation for analysis and/or classification, and output result data. In this way, in order for the neural network to accurately output the result data corresponding to the input data, it is necessary to train the neural network.

'Training' refers to a method of inputting various data into a neural network, analyzing the input data, a method of classifying the input data, and/or a method of extracting features necessary for generating result data from the input data, etc. may mean training the neural network so that the neural network can discover or learn on its own. Specifically, through the learning process, the neural network may be set by optimizing the weight values inside the neural network by training the learning data (eg, a plurality of different images). Then, by learning the input data by itself through a neural network having an optimized weight value, a desired result is output.

Specifically, the neural network is classified as a deep neural network when the number of hidden layers that are internal layers for performing the operation is plural, that is, when the depth of the neural network for performing the operation increases. can Examples of neural networks include Convolutional Neural Network (CNN), Deep Neural Network (DNN), Recurrent Neural Network (RNN), Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Bidirectional Recurrent Deep Neural Network (BRDNN), and deep Q-networks (Deep Q-Networks), and the like, are not limited to the above-described example. Also, the neural network can be subdivided. For example, the CNN neural network may be subdivided into a Deep Convolution Neural Network (DCNN) or a Capsnet neural network (not shown).

In the disclosed embodiment, the 'AI model' may refer to a neural network including at least one layer that receives input data and operates to output a desired result. In addition, an 'AI model' is an algorithm or a set of a plurality of algorithms that outputs a desired result by performing an operation through a neural network, a processor for executing such an algorithm or a set thereof, executing this algorithm or a set thereof It may mean software for, or hardware for executing such an algorithm or a set thereof.

Referring to FIG. 11 , the neural network 1110 may be trained by receiving training data. Then, the learned neural network 1110 receives the input data 1111 from the input terminal 1120, analyzes the input data 1111, and performs an operation to output the output data 1115, which is a desired result, the output terminal 1140 ) can be done in An operation through the neural network may be performed through a hidden layer 1130 . 11 , the hidden layer 1130 is simplified to be formed as a single layer for convenience, but the hidden layer 1130 may be formed as a plurality of layers.

Specifically, in the disclosed embodiment, the neural network 1110 may learn gain values of a signal that change according to the relative position of the drone with respect to the antenna of the vehicle. The learned neural network 1110 may receive vehicle location information and calculate relative coordinates for the optimal drone location that guarantees communication quality.

In the disclosed embodiment, the neural network for outputting the above-described information for controlling the drone may be implemented in a processor (eg, 130 in FIGS. 9A and 9B ).

Alternatively, the neural network for outputting the above-described information for controlling the drone may be implemented in an antenna device for a vehicle that is distinguished from the electronic device 100, a separate electronic device (not shown) located in the vehicle, or a processor (not shown). can

In addition, the above-described operation through the neural network may be performed in a server (not shown) capable of communicating with the electronic device of the vehicle through a wireless communication network according to the disclosed embodiment. Communication between the electronic device and the server (not shown) will be described in detail below with reference to FIGS. 12 and 13 .

12 is a diagram illustrating an electronic device according to a disclosed embodiment that operates in conjunction with a server. The server 1210 may include a server, a server system, a server-based device, etc. that transmit and receive data to and from an electronic device, for example, the vehicle electronic device 1250 through a communication network and process data.

Specifically, the vehicle electronic device 1250 is an electronic device located in the vehicle 1200 and may be the electronic device 100 according to the disclosed embodiment.

Alternatively, the vehicle electronic device 1250 may be a separate electronic device located in the vehicle 1200 and capable of performing wired/wireless communication with the electronic device 100 . The vehicle electronic device 1250 may perform beamforming by adjusting phase values of at least one radio signal output from a plurality of antenna elements included in the array antenna.

In the disclosed embodiment, the server 1210 may include a communication unit that communicates with the vehicle electronic device 1250 and a processor that performs at least one instruction.

When the communication state between the vehicle electronic device 1250 and the base station deteriorates, the processor of the server 1210 may control the communication unit to perform communication between the vehicle electronic device 1250 and the base station through the drone.

In the disclosed embodiment, the server 1210 may control the drone by performing an operation through the neural network described with reference to FIG. 11 , and may control communication between the drone and the base station and the vehicle electronic device 1250 . Specifically, the server 1210 may train an AI model and store the trained AI model. And, the server 1210 may acquire the above-described phase information using the trained AI model.

In general, the vehicle electronic device 1250 may have more limited memory storage capacity, computational processing speed, and collection capability of the learning data set compared to the server 1210 . Accordingly, after storage of large data and operations requiring large amounts of computation are performed by the server 1210 , necessary data and/or a used AI model may be transmitted to the vehicle electronic device 1250 through a communication network. Then, the vehicle electronic device 1250 may receive and use necessary data and/or an AI model through a server, without a processor having a large amount of memory and a fast computing power, to quickly and easily perform a necessary operation.

In the disclosed embodiment, the server 1210 may include the neural network 1110 described with reference to FIG. 11 . Specifically, the neural network 1110 included in the server 1210 performs at least one of i) determining whether NLOS is present, ii) determining the location of the drone, and iii) determining whether to perform handover. One action can be performed.

13 is a diagram for describing FIG. 12 in detail. In FIG. 13 , the same components as in FIGS. 13 and 12 are illustrated using the same reference numerals. Accordingly, in describing the components of FIG. 13 , descriptions overlapping with the above descriptions will be omitted.

The communication unit 1340 communicates with an external device (eg, a server) through at least one wireless communication network 1201 . Here, the external device (not shown) includes a server (eg, 1210) that can perform at least one of operations performed in the vehicle electronic device 1250 or transmit/receive data required for the vehicle electronic device 1250, etc. can be

Also, the communication unit 1340 includes at least one communication module such as a short-range communication module, a wired communication module, a mobile communication module, and a broadcast reception module. Here, the at least one communication module is a tuner that performs broadcast reception, Bluetooth, Wireless LAN (WLAN) (Wi-Fi), Wibro (Wireless broadband), Wimax (World Interoperability for Microwave Access), CDMA, WCDMA, Internet, 3G , 4G, and/or 5G, refers to a communication module capable of transmitting and receiving data through a network conforming to a communication standard such as a method of performing communication using millimeter wave (mmWAVE).

For example, when the communication unit 1340 performs communication using a millimeter wave (mmWAVE), a large amount of data can be quickly transmitted and received. Specifically, by rapidly receiving large amounts of data in the vehicle, data necessary for vehicle safety (eg, data necessary for autonomous driving, data necessary for navigation service, etc.), user-use content (eg, movies, music, etc.) etc.), it is possible to increase the safety of the vehicle and/or the convenience of the user.

Specifically, the mobile communication module included in the communication unit 1340 communicates with another device (eg, a server (not shown)) located at a remote location through a communication network conforming to a communication standard such as 3G, 4G, and/or 5G. communication can be performed. Also, although the communication unit 1340 and the array antenna 1310 are illustrated as separate components in FIG. 13 , the communication unit 1340 may include the array antenna 1310 . Specifically, at least one communication module included in the communication unit 1340 may include an array antenna 1310 for transmitting and receiving radio waves.

Referring to FIG. 13 , the server 1210 may include a communication unit 1330 and a processor 1350 . In addition, the server 1210 may further include a DB 1360 .

The communication unit 1330 may include one or more components that allow communication with the vehicle electronic device 1250 . Since the detailed configuration of the communication unit 1330 corresponds to the configuration of the above-described communication unit 1340 , a detailed description thereof will be omitted.

For example, the communication unit 1330 communicates with another device (eg, vehicle electronic device 1250) located at a remote location through a communication network conforming to a communication standard such as the Internet, 3G, 4G, and/or 5G. It may include at least one communication module that performs the

The processor 1350 controls the overall operation of the server 1210 . For example, the processor 1350 may perform at least one instruction of the server 1210 and at least one of programs to perform required operations.

In addition, the DB 1360 may include a memory (not shown), and can store at least one of at least one instruction, program, and data necessary for the server 1210 to perform a predetermined operation in the memory (not shown). there is. Also, the DB 1360 may store data necessary for the server 1210 to perform an operation according to the neural network.

Specifically, in the disclosed embodiment, the server 1210 may store the neural network 1110 described with reference to FIG. 11 . The neural network 1110 may be stored in at least one of the processor 1350 and the DB 1360 . The neural network 1110 included in the server 1210 may be a neural network that has been trained.

In the disclosed embodiment, the server 1210 may support wireless communication through a drone using an internally included neural network.

Also, the server 1210 may transmit the learned neural network to the communication unit 1340 of the vehicle electronic device 1250 through the communication unit 1330 . Then, the vehicle electronic device 1250 may acquire and store the neural network on which learning has been completed, and may acquire target output data through the neural network.

14 is a diagram illustrating an example of learning and recognizing data by interworking with an electronic device for a vehicle and a server according to an embodiment of the present disclosure;

The electronic device for a vehicle according to an embodiment of the present disclosure may support wireless mobile communication using artificial intelligence by interworking with a server. For example, the electronic device for a vehicle may use artificial intelligence in analyzing surrounding environment information, controlling a drone, or changing a communication state. Referring to FIG. 14 , the server 1210 may learn a criterion for determining the situation, controlling the drone, and/or changing the communication state, and the electronic device 1250 for the vehicle is a situation based on the learning result by the server 1210 . can be judged

The data learning unit 1450 included in the server 1210 according to an embodiment of the present disclosure may learn a criterion for determining a situation, controlling a drone, and/or changing a communication state. The data learning unit 1450 may learn a criterion regarding which data to use to make a decision and how to make a decision using the data. The data learning unit 1450 may learn criteria for situation determination, drone control, and/or communication state change by acquiring data to be used for learning and applying the acquired data to a data recognition model.

The data recognition unit 1420 included in the electronic device for a vehicle 1250 according to an embodiment of the present disclosure may determine a situation based on data, control a drone, or change a communication state. The data recognition unit 1420 may recognize a situation from predetermined data by using the learned data recognition model. The data recognition unit 1420 acquires predetermined data according to a preset criterion by learning and uses the data recognition model using the acquired data as an input value to determine a predetermined situation based on the predetermined data or to operate the drone. You can control or change the communication status. In addition, a result value output by the data recognition model using the obtained data as an input value may be used to update the data recognition model.

At least one of the data learning unit 1450 and the data recognition unit 1420 may be manufactured in the form of at least one hardware chip and mounted on the vehicle electronic device 1250 or the server 1210 . For example, at least one of the data learning unit 1450 and the data recognition unit 1420 may be manufactured in the form of a dedicated hardware chip for artificial intelligence, or an existing general-purpose processor (eg, CPU or application processor) or graphics. It may be manufactured as a part of a dedicated processor (eg, GPU) and mounted on the various electronic devices described above.

The data learner 1450 and the data recognizer 1420 may provide model information built by the data learner 1450 to the data recognizer 1420 through a wired or wireless connection, or the data recognizer 1420 . Data input as , may be provided to the data learning unit 1450 as additional learning data.

Meanwhile, at least one of the data learning unit 1450 and the data recognition unit 1420 may be implemented as a software module. When at least one of the data learning unit 1450 and the data recognition unit 1420 is implemented as a software module (or a program module including instructions), the software module is a computer-readable non-transitory readable It may be stored in a recording medium (non-transitory computer readable media). Also, in this case, at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, a part of the at least one software module may be provided by an operating system (OS), and the other part may be provided by a predetermined application.

The data learning unit 1450 according to an embodiment includes a data acquiring unit 1450-1, a preprocessing unit 1450-2, a training data selection unit 1450-3, a model learning unit 1450-4, and a model evaluation. part 1450-5 may be included.

The data acquisition unit 1450-1 may acquire data necessary for situation determination, drone control, and/or communication status change.

For example, the data acquisition unit 1450-1 may receive a measurement value related to communication quality, whether there are available drones in or around the vehicle, location information of the drone, location information of the vehicle, and the like.

The preprocessor 1450 - 2 may preprocess the acquired data so that the acquired data can be used for situation determination, drone control, and/or learning for changing a communication state. The preprocessor 1450-2 may process the acquired data into a preset format so that the model learning part 1450-4, which will be described later, uses the acquired data for learning.

The learning data selection unit 1450 - 3 may select data necessary for learning from among the preprocessed data. The selected data may be provided to the model learning unit 1450 - 4 . The learning data selection unit 1450 - 3 may select data required for learning from among preprocessed data according to a preset criterion. In addition, the training data selection unit 1450-3 may select data according to a preset criterion by learning by the model learning unit 1450-4, which will be described later.

The model learning unit 1450-4 determines how to determine the situation, how to control the drone, or how to change the communication state (eg, whether to use the drone as a relay node, or the hand It is possible to learn the criteria for whether to perform over or not). Also, the model learning unit 1450 - 4 may learn a criterion for which learning data to use for situation determination, drone control, and/or communication state change.

As an example, the model learning unit 1450 - 4 may learn a criterion for determining the moving position of the drone by learning a gain measurement index and a relative position of the drone with respect to the vehicle.

Also, the model learning unit 1450 - 4 may learn a data recognition model used for situation determination, drone control, and/or communication state change by using the learning data. In this case, the data recognition model may be a pre-built model. For example, the data recognition model may be a model built in advance by receiving basic training data (eg, simulation results related to mmWave communication between a car antenna and a drone).

The data recognition model may be constructed in consideration of the field of application of the recognition model, the purpose of learning, or the computer performance of the device. The data recognition model may be, for example, a model based on a neural network. For example, a model such as a Convolutional Neural Network (CNN), a Deep Neural Network (DNN), a Recurrent Neural Network (RNN), or a Bidirectional Recurrent Deep Neural Network (BRDNN) may be used as the data recognition model, but is not limited thereto.

The model evaluation unit 1450-5 inputs evaluation data to the data recognition model, and when the recognition result output from the evaluation data does not satisfy a predetermined criterion, the model learning unit 1450-4 can learn again. there is. In this case, the evaluation data may be preset data for evaluating the data recognition model.

For example, the model evaluator 1450-5 sets a predetermined criterion when the number or ratio of the evaluation data for which the recognition result is not accurate among the recognition results of the learned data recognition model for the evaluation data exceeds a preset threshold. It can be evaluated as unsatisfactory.

On the other hand, at least one of the data acquisition unit 1450-1, the preprocessor 1450-2, the training data selection unit 1450-3, the model learning unit 1450-4, and the model evaluation unit 1450-5 is It may be implemented as a software module. At least one of the data acquisition unit 1450-1, the preprocessor 1450-2, the training data selection unit 1450-3, the model learning unit 1450-4, and the model evaluation unit 1450-5 is a software module When implemented as (or, a program module including instructions), the software module may be stored in a computer-readable non-transitory computer readable medium. Also, in this case, at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, a part of the at least one software module may be provided by an operating system (OS), and the other part may be provided by a predetermined application.

Meanwhile, referring to FIG. 14 , the data recognition unit 1420 according to an embodiment includes a data acquisition unit 1420-1, a preprocessor 1420-2, a recognition data selection unit 1420-3, and a recognition result It may include a study 1420-4 and a model updater 1420-5.

The data acquisition unit 1420-1 may acquire data necessary for situation determination, drone control, and/or communication status change. The preprocessor 1420 - 2 may preprocess the acquired data so that the acquired data can be used for situation determination, drone control, and/or communication state change. The preprocessor 1420-2 may process the acquired data into a preset format so that the recognition result providing unit 1420-4, which will be described later, uses the acquired data.

The recognition data selection unit 1420-3 may select data necessary for situation determination, drone control, and/or communication state change from among the pre-processed data. The selected data may be provided to the recognition result providing unit 1420 - 4 . The recognition data selection unit 1420-3 may select some or all of the pre-processed data according to a preset criterion for situation determination, drone control, and/or communication state change. Also, the recognition data selection unit 1420-3 may select data according to a preset criterion by learning by the model learning unit 1450-4 to be described above.

The recognition result providing unit 1420-4 of the vehicle electronic device 1250 applies the data selected by the recognition data selection unit 1420-3 to the data recognition model generated by the server 1210 to determine the situation or use the drone. control or change the communication status. The recognition result providing unit 1420 - 4 may provide a recognition result according to the purpose of data recognition. The recognition result providing unit 1420 - 4 may apply the selected data to the data recognition model by using the data selected by the recognition data selecting unit 1420 - 3 as an input value. Also, the recognition result may be determined by a data recognition model.

As an example, the recognition result providing unit 1420-4 provides a recognition result including a measurement value related to communication quality, whether there are drones available in or around the vehicle, location information of the drone, location information of the vehicle, etc. can provide

The model updating unit 1420 - 5 may update the data recognition model based on the evaluation of the recognition result provided by the recognition result providing unit 1420 - 4 . For example, the model updating unit 1420-5 provides the recognition result provided by the recognition result providing unit 1420-4 to the model learning unit 1450-4, so that the model learning unit 1450-4 is The data recognition model can be updated.

Meanwhile, in the data recognition unit 1420 , a data acquisition unit 1420-1, a preprocessor 1420-2, a recognition data selection unit 1420-3, a recognition result providing unit 1420-4, and a model update unit ( 1420-5) may be manufactured in the form of at least one hardware chip and mounted in an electronic device. For example, among the data acquisition unit 1420-1, the preprocessor 1420-2, the recognition data selection unit 1420-3, the recognition result providing unit 1420-4, and the model update unit 1420-5 At least one may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or may be manufactured as part of an existing general-purpose processor (eg, CPU or application processor) or graphics-only processor (eg, GPU). It may be mounted on one various electronic devices.

In addition, at least one of the data acquisition unit 1420-1, the preprocessor 1420-2, the recognition data selection unit 1420-3, the recognition result providing unit 1420-4, and the model update unit 1420-5 may be implemented as a software module. At least one of the data acquisition unit 1420-1, the preprocessor 1420-2, the recognition data selection unit 1420-3, the recognition result providing unit 1420-4, and the model update unit 1420-5 is software. When implemented as a module (or a program module including instructions), the software module may be stored in a computer-readable non-transitory computer readable medium. Also, in this case, at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, a part of the at least one software module may be provided by an operating system (OS), and the other part may be provided by a predetermined application. The disclosed embodiments provide computer-readable storage media ) can be implemented as a S/W program including instructions stored in

A computer is an apparatus capable of calling a stored instruction from a storage medium and operating according to the called instruction according to the disclosed embodiment, and may include the terminal device and the remote control device according to the disclosed embodiment.

The computer-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' means that the storage medium does not include a signal and is tangible, and does not distinguish that data is semi-permanently or temporarily stored in the storage medium.

Also, the electronic device or method according to the disclosed embodiments may be included in a computer program product and provided. Computer program products may be traded between sellers and buyers as commodities.

The computer program product may include a S/W program and a computer-readable storage medium in which the S/W program is stored. For example, computer program products may include products (eg, downloadable apps) in the form of S/W programs distributed electronically through manufacturers of electronic devices or electronic markets (eg, Google Play Store, App Store). there is. For electronic distribution, at least a portion of the S/W program may be stored in a storage medium or may be temporarily generated. In this case, the storage medium may be a server of a manufacturer, a server of an electronic market, or a storage medium of a relay server temporarily storing a SW program.

The computer program product may include a storage medium of a server or a storage medium of a terminal in a system including a server and a terminal (eg, an electronic device or an electronic device for a vehicle). Alternatively, when there is a third device (eg, a smart phone) that is communicatively connected to the server or terminal, the computer program product may include a storage medium of the third device. Alternatively, the computer program product may include the S/W program itself transmitted from the server to the terminal or the third device, or transmitted from the third device to the terminal.

In this case, one of the server, the terminal, and the third device may execute the computer program product to perform the method according to the disclosed embodiments. Alternatively, two or more of the server, the terminal, and the third device may execute the computer program product to distribute the method according to the disclosed embodiments.

For example, a server (eg, a cloud server or an artificial intelligence server, etc.) may execute a computer program product stored in the server, and may control a terminal communicatively connected with the server to perform the method according to the disclosed embodiments. As another example, the third device may execute a computer program product to control the terminal communicatively connected to the third device to perform the method according to the disclosed embodiment.

When the third device executes the computer program product, the third device may download the computer program product from the server and execute the downloaded computer program product. Alternatively, the third device may execute the computer program product provided in a preloaded state to perform the method according to the disclosed embodiments.

Claims

A method mounted on a vehicle and performed by an electronic device supporting wireless communication for the vehicle,

performing communication with the base station by accessing the base station;

controlling the drone by transmitting information related to the location of the drone based on the determination that the communication state with the base station has deteriorated; and

and performing communication between the electronic device and the base station via the drone.
According to claim 1,

The step of controlling the drone,

determining that the communication state with the base station has deteriorated based on the strength of the signal received from the base station; and

Based on the determination that the communication state with the base station has deteriorated, comprising the step of transmitting information related to the location of the drone to the drone.
According to claim 1,

Information related to the location of the drone,

and a three-dimensional coordinate value determined according to a predetermined criterion based on the position of the vehicle.
According to claim 1,

The step of controlling the drone,

determining whether there are drones available in the vehicle based on the determination that the communication state with the base station has deteriorated;

maintaining communication with the base station when there is no drone available; and

When there is the available drone, transmitting information related to the location of the drone to the drone to control the drone.
According to claim 1,

The drone and the electronic device are connected in a D2D communication method,

The method, characterized in that the electronic device performs communication with the base station by using the drone as a relay node.
An electronic device mounted on a vehicle to support wireless communication for the vehicle, the electronic device comprising:

a transceiver for transmitting and receiving signals to and from the base station and the drone;

a memory for storing programs and data for operation of the electronic device; and

By executing the program stored in the memory,

communicate with the base station by accessing the base station;

Based on the determination that the communication state with the base station has deteriorated, by transmitting information related to the location of the drone to control the drone,

An electronic device comprising at least one processor configured to perform communication between the electronic device and the base station through the drone.
7. The method of claim 6,

The at least one processor,

Based on the strength of the signal received from the base station, it is determined that the communication state with the base station is bad,

Based on the determination that the communication state with the base station has deteriorated, the electronic device characterized in that it transmits information related to the location of the drone to the drone.
7. The method of claim 6,

Information related to the location of the drone,

and a three-dimensional coordinate value determined according to a predetermined criterion based on the position of the vehicle.
7. The method of claim 6,

the at least one processor,

Based on the determination that the communication state with the base station has deteriorated, it is determined whether there are drones available in the vehicle,

If there is no drone available, continue to communicate with the base station,

When there is the available drone, the electronic device characterized in that the drone is controlled by transmitting information related to the location of the drone to the drone.
7. The method of claim 6,

The drone and the electronic device are connected in a D2D communication method,

The electronic device is characterized in that it performs communication with the base station by using the drone as a relay node.
7. The method of claim 6,

the at least one processor,

transmits control information to the drone so that the drone establishes a connection for communication between the base stations;

performing a discovery process for D2D connection with the drone,

Establish a D2D connection with the drone,

An electronic device, characterized in that for transmitting data to the base station through the drone.
7. The method of claim 6,

the at least one processor,

receiving a measurement report from the drone,

Determining whether to handover based on the measurement report,

The measurement report includes at least one of RSRP, RSRQ, and RS-SINR.
13. The method of claim 12,

the at least one processor,

Based on the decision to perform handover, determining whether to continue using the drone,

When it is decided to continue using the drone, a handover is performed through the drone,

When it is determined to use a drone other than the drone, location-related information is transmitted to the other drone, and communication between other base stations is performed through the other drone.
7. The method of claim 6,

The electronic device is

An electronic device, characterized in that it communicates with at least one of the base station and the drone using a millimeter wave (mmWave).
In one or more computer-readable recording media in which a program mounted on a vehicle to perform a method performed by an electronic device supporting wireless communication for the vehicle is stored,

The method is

performing communication with the base station by accessing the base station;

controlling the drone by transmitting information related to the location of the drone based on the determination that the communication state with the base station has deteriorated; and

A computer-readable recording medium comprising the step of performing communication between the electronic device and the base station through the drone.