Area optimization device, remote control device, system, optimization method and program

Abstract

This system provides an optimization method that can expand service area coverage, which is affected by terrain-related interference such as radio wave blockage and diffraction losses, while also reducing the computational load required for that optimization. [Solution] For each of the multiple candidate locations in the sky where multiple aerial PFs can be placed, the system acquires data on the radio wave propagation characteristics of the radio wave propagation path between the candidate location and the service area, based on the geographical characteristics of the service area. Based on the radio wave propagation characteristics data, it determines the locations of the multiple aerial PFs that will form cells toward the service area, or both the number and locations of the multiple aerial PFs. Based on the radio wave propagation characteristics data, it determines the values ​​of the beam parameters to be used to form cells for the multiple aerial PFs.

Description

[Technical Field]

[0001] This disclosure relates to the optimization of the service area of ​​mobile communications by beamforming directed from the antenna of a relay communication station mounted on an aerial PF such as HAPS towards the ground or sea. [Background technology]

[0002] Conventionally, methods are known for optimizing the antenna parameters of a service link (e.g., beam direction and width for cell formation) so that a desired communication quality (e.g., throughput) can be obtained over the entire service area (hereinafter simply referred to as "area") formed on land or at sea by repeater-type or base station-type relay communication stations mounted on high-altitude platform stations (HAPS) (also called "high-altitude pseudo-satellites") located in the upper atmosphere, low Earth orbit (LEO) satellites, geostationary orbit (GEO) satellites, etc. (see Patent Documents 1-4 and Non-Patent Documents 1-3). [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-161734 [Patent Document 2] Japanese Patent Publication No. 2022-161742 [Patent Document 3] Patent No. 7318047 [Patent Document 4] Patent No. 7108737 [Non-patent literature]

[0004] [Non-Patent Document 1] Y. Shibata, N. Kanazawa, M. Konishi, K. Hoshino, Y. Ohta and A. Nagate, "System Design of Gigabit HAPS Mobile Communications," in IEEE Access, vol. 8, pp. 157995-158007, 2020. [Non-Patent Document 2] Yohei Shibata, Wataru Takabatake, Kenji Hoshino, Atsushi Nagate and Tomoaki Ohtsuki, "Two-Step Dynamic Cell Optimization Algorithm for HAPS Mobile Communications", IEEE Access, vol. 10, pp.68085-68098, 2022. [Non-Patent Document 3] W. Takabatake, Y. Shibata, K. Hoshino, and T. Ohtsuki, "Time-Efficient Neural-Network-Based Dynamic Area Optimization Algorithm for High-Altitude Platform Station Mobile Communications", Future Internet 2024, vol. 16, no. 9, 332, 2024. [Overview of the project]

[0005] An area optimization device according to one aspect of the present disclosure is an area optimization device that optimizes the service area of ​​mobile communications by a plurality of aerial PFs (platforms) equipped with relay station antennas capable of beamforming control to form one or more cells toward the ground. This area optimization device includes: a data acquisition unit that acquires data on the radio wave propagation characteristics of the radio wave propagation path between each of a plurality of aerial candidate points where the plurality of aerial PFs can be placed, based on the geographical characteristics of the service area; a first optimization unit that determines the positions of the plurality of aerial PFs that form the cells toward the service area, or both the number and positions of the plurality of aerial PFs, based on the radio wave propagation characteristics data; and the first optimization unit that optimizes the area optimization device based on the radio wave propagation characteristics data. The position or the The system includes a second optimization unit that determines the values ​​of beam parameters used to form the cells for each of the multiple upper-air PFs after both their number and position have been determined.

[0006] In the area optimization device, the data acquisition unit acquires radio wave propagation loss data of the radio wave propagation path between each of the plurality of candidate placement points and the service area based on geographical features including the topography of the service area; the first optimization unit determines the positions of the plurality of aerial PFs or both the number and positions of the plurality of aerial PFs based on the radio wave propagation loss data to maximize the area in the service area where the received strength index value is equal to or greater than a reference value; and the second optimization unit may determine the values ​​of beam parameters used to form the cell for each of the plurality of aerial PFs after the positions or both the number and positions have been determined by the first optimization unit to maximize the area in the service area where the received strength index value is equal to or greater than a reference value.

[0007] In the area optimization device, the radio wave propagation loss data is propagation loss data relating to loss caused by at least one of radio wave blocking and diffraction due to the terrain of the service area, and the received intensity index value is the service workmanThis may also be the reference signal reception power (RSRP) of the terminal device at the rear.

[0008] In the area optimization device, the plurality of upper air PFs are divided into a plurality of groups, and the first optimization unit determines, for each group, the positions of the plurality of upper air PFs forming the cell or both the number and positions of the plurality of upper air PFs based on the radio wave propagation characteristics data, and the second optimization unit determines, for each group, the beam parameter values ​​for the plurality of upper air PFs after the positions or both the number and positions have been determined by the first optimization unit, based on the radio wave propagation characteristics data.

[0009] In the area optimization device, the data acquisition unit may acquire the radio wave propagation characteristics data by pre-calculating it within the device itself or by receiving it from an external device.

[0010] A system according to another aspect of the present disclosure comprises one of the area optimization devices described above, and a plurality of upper PFs whose positions or the number and positions are determined by the area optimization device. Each of the plurality of upper PFs applies the beam parameter setting value corresponding to the upper PF, determined by the second optimization unit of the area optimization device, to the formation of the cell.

[0011] In the above system, the area optimization device is provided in one of the multiple upper air PFs, and the one upper air PF may include a transmitting unit that transmits the beam parameter values ​​corresponding to the other upper air PFs to the other upper air PFs.

[0012] The system may further include a remote control device capable of communicating with each of the plurality of upper PFs, the remote control device having the area optimization device and a transmitting unit that transmits the beam parameter values ​​corresponding to the upper PF to each of the plurality of upper PFs.

[0013] A remote control device according to yet another aspect of the present disclosure is a remote control device capable of communicating with each of a plurality of aerial platforms (PFs) equipped with antennas of a relay communication station that are beamforming controllable to form one or more cells toward the ground. The remote control device comprises an area optimization device and a transmitting unit that transmits set values ​​of the beam parameters corresponding to the aerial PF to each of the plurality of aerial PFs that form the cells toward the service area.

[0014] A method relating to yet another aspect of the present disclosure is a method for optimizing a plurality of aerial platforms (PFs) equipped with beamforming controllable antennas of a relay communication station to form one or more cells toward a ground service area. This optimization method includes: for each of a plurality of aerial candidate locations where the plurality of aerial PFs can be placed, acquiring data on the radio wave propagation characteristics of the radio wave propagation path between the candidate location and the service area, based on the geographical characteristics of the service area; performing a first optimization to determine the positions of the plurality of aerial PFs that form the cells toward the service area, or both the number and positions of the plurality of aerial PFs, based on the radio wave propagation characteristics data; and performing a second optimization to determine the beam parameter values ​​to be used for forming the cells for each of the plurality of aerial PFs after the positions or both the number and positions have been determined in the first optimization, based on the radio wave propagation characteristics data.

[0015] A program according to still another aspect of the present disclosure is a program executed by a computer or a processor provided in a remote control device that can communicate with each of a plurality of aerial Platforms (PFs) equipped with antennas of a relay communication station capable of beamforming control to form one or more cells toward a ground service area. This program includes, for each of a plurality of aerial placement candidate points in the sky where the plurality of aerial PFs can be placed, program code for acquiring data on the radio wave propagation characteristics of the radio wave propagation path between the placement candidate point and the service area based on the geographical characteristics of the service area, program code for determining the positions of the plurality of aerial PFs forming the cell or both the number and positions of the plurality of aerial PFs toward the service area based on the data on the radio wave propagation characteristics, and program code for determining the values of beam parameters used for forming the cell for each of the plurality of aerial PFs after determining the position or both the number and position by the first optimization unit based on the data on the radio wave propagation characteristics.

[0016] All or part of the program may include a learned model created by machine learning.

Brief Description of the Drawings

[0017] [Figure 1] FIG. 1 is an explanatory diagram showing an example of a service area composed of a plurality of cells formed by an aerial PF (HAPS) according to an embodiment. [Figure 2] FIG. 2(a) is an explanatory diagram showing an example of the cell arrangement and user terminal distribution before applying area optimization control in a service area composed of three cells. FIG. 2(b) is an explanatory diagram showing an example of the cell arrangement after applying the area optimization control. [Figure 3] FIG. 3 is an explanatory diagram showing an example of antenna tilt angle, horizontal half-power beamwidth, and vertical half-power beamwidth as beam parameters (antenna parameters) used for area optimization control. [Figure 4]Figure 4 is an explanatory diagram showing an example of radio wave shielding and diffraction due to terrain in the service area of ​​an upper-air PF (HAPS). [Figure 5] Figure 5 is an explanatory diagram showing an example of a reference signal received power (RSRP) heatmap of a user terminal, taking into account the effects of terrain when an aerial PF (HAPS) is placed above a mountainous area. [Figure 6] Figure 6 is an explanatory diagram showing an example of the arrangement of multiple aerial PFs (HAPS) in a communication system according to the embodiment. [Figure 7] Figure 7 is a flowchart showing an example of area optimization control that takes into account geographical features, including the topography of the service area, in an area optimization device provided in a communication system according to the embodiment. [Figure 8] Figure 8 is a block diagram showing an example configuration of an area optimization device included in a communication system according to this embodiment. [Modes for carrying out the invention]

[0018] Embodiments of this disclosure will be described below with reference to the drawings. Note that each drawing is merely a schematic representation of the shape, size, positional relationships, correspondences, configuration, processing, steps, etc., to the extent that the contents of this disclosure can be understood. Therefore, this disclosure is not limited to the shapes, sizes, positional relationships, correspondences, configurations, processing, steps, and steps exemplified in each drawing. Furthermore, the numerical values ​​exemplified in this disclosure are merely preferred examples, and therefore, this disclosure is not limited to the numerical values ​​exemplified.

[0019] The system according to the embodiment described in this book is a communication system equipped with an area optimization device that optimizes the service area of ​​mobile communications using multiple aerial PFs (platforms) equipped with relay station antennas capable of beamforming control to form one or more cells toward the ground. The area optimization device of this embodiment acquires data on the radio wave propagation characteristics of the radio wave propagation path between the candidate placement point and the service area (e.g., propagation loss data) based on the geographical features of the service area (e.g., terrain) for each of the multiple candidate placement points in the air where multiple aerial PFs can be placed, and performs two-stage optimization, first optimization and second optimization, based on the radio wave propagation characteristics data. In the first optimization, the positions of the multiple aerial PFs that form cells toward the service area are determined, or both the number and positions of the multiple aerial PFs are determined, based on the radio wave propagation characteristics data. In the second optimization, the beam parameter values ​​used to form cells for the multiple aerial PFs whose positions or both the number and positions were determined in the first optimization are determined, based on the radio wave propagation characteristics data. By performing optimization in two stages, first and second optimization, it is possible to expand the coverage of wide-area service areas where radio wave blockage and diffraction losses occur due to terrain effects, while also reducing the computational load required for service area optimization.

[0020] Figure 1 is an explanatory diagram showing an example of the overall configuration of a communication system according to this embodiment. The communication system according to this embodiment is suitable for realizing a 3D network of fifth-generation or later mobile communications that can handle simultaneous connection to a large number of terminal devices (hereinafter referred to as "UEs") 61 and low latency. Furthermore, the mobile communications standards applicable to the communication system, radio relay station, base station, repeater and UE disclosed herein include fifth-generation mobile communications standards and standards for fifth-generation and subsequent generations of mobile communications.

[0021] As shown in Figure 1, the communication system includes, for example, a High Altitude Platform Station (HAPS) 10 (also called a "High Altitude Pseudo-Satellite" or "Stratospheric Platform") as an airborne relay-type communication relay device (wireless relay device) that constitutes an airborne platform. The HAPS 10 is an airborne relay-type, airborne stationary-type, or airborne levitation-type communication relay device, located in the airspace at a predetermined altitude, and forms a 3D cell (3D area) in the target airspace at a predetermined altitude toward the target service area 20A. Although Figure 1 illustrates an example configuration in which a single HAPS 10 is placed in the air, the communication system of this embodiment can also be applied when two or more HAPS 10 are placed in the air.

[0022] HAPS10 is a flying or floating vehicle 100 equipped with a relay communication station 110, which is controlled by autonomous or external control to float or fly in high-altitude airspace (float airspace) at an altitude of 100 km or less above the ground or sea surface. The airspace in which HAPS10 is located may be, for example, stratospheric airspace with an altitude H of 18 km or more and 50 km or less. This airspace may also be airspace with relatively stable weather conditions at an altitude of 15 km or more and 25 km or less, and in particular, airspace at an altitude of approximately 20 km.

[0023] The target airspace for cell formation in HAPS10 may be a predetermined altitude range (for example, an altitude range of 50[m] to 1000[m]) located between the airspace where HAPS10 is located and the near-ground cell formation area covered by conventional base stations such as macrocell base stations (e.g., LTE eNodeB or next-generation gNodeB).

[0024] The target airspace for cell formation may be over the sea, a river, or a lake. Furthermore, the three-dimensional cells formed by HAPS10 may be configured to reach the ground or sea surface to enable communication with UE61 located on land or at sea.

[0025] HAPS10 communicates wirelessly with UE61 via a service link antenna (also called an "SL antenna") 111 of a relay communication station 110 installed on an aircraft 100 such as a flying object or floating object located in the air. HAPS10 can fly on electricity, for example, by being equipped with at least one of a battery and a solar power generation system. HAPS10 may be a solar-powered plane type HAPS as shown in the illustration, or an airship type HAPS. Furthermore, the HAPS10 on which the relay communication station 110 is installed may be an artificial satellite (e.g., a communications satellite), a balloon, or an unmanned aerial vehicle (UAV) such as a drone or UAS (Unmanned Aircraft Systems). HAPS10 may also fly using at least one of a battery and an engine as a power source. The UAV may be, for example, an unmanned aircraft that flies on fuel, or a drone that flies on a battery or the like.

[0026] The relay communication station 110 includes a service link antenna (SL antenna) 111 and a feeder link antenna (hereinafter also referred to as "FL antenna") 112. The relay communication station 110 can communicate with the UE 61 via the SL antenna 111 using the service link SL. The SL antenna 111 is, for example, a beamforming controllable array antenna that can control the direction and width of each of the multiple beams that form multiple cells 20C(1) to 20C(7) in the target service area 20A. The regions through which the beams pass in the cell formation target airspace are the three-dimensional cells 20C(1) to 20C(7). Multiple beams adjacent to each other in the cell formation target airspace may partially overlap. Furthermore, the multiple communication areas where the multiple cells 20C(1) to 20C(7) reach the ground (or sea, etc.) are the footprints 20F(1) to 20F(7).

[0027] In the illustrated example, seven cells 20C(1) to 20C(7) are formed via the SL antenna 111, but the number of cells 20C can be single, two to six, or eight or more.

[0028] The SL antenna 111 is, for example, a single or multiple array antenna in which multiple antenna elements are arranged two-dimensionally or three-dimensionally, and which is capable of forming multiple beams toward the ground. The SL antenna 111 may also be a Massive antenna in which a large number of antenna elements are arranged two-dimensionally and the beam directivity in the horizontal and vertical directions can be controlled.

[0029] The relay communication station 110 can communicate via feeder link FL with a gateway device for HAPS (also called a "feeder station"; hereinafter referred to as a "GW station") 70 located on land (or at sea, etc.) via the FL antenna 112. The FL antenna 112 is, for example, an array antenna whose directivity (direction of the directional beam) can be controlled. The FL antenna 112 is, for example, one or more array antennas in which multiple antenna elements are arranged two-dimensionally or three-dimensionally. The FL antenna 112 may also be a Massive antenna in which many antenna elements are arranged two-dimensionally and whose horizontal and vertical directivity can be controlled. In the figure, feeder link FL(F) is a forward link from GW station 70 to UE61 via HAPS 10, and feeder link FL(R) is a reverse link from UE61 to GW station 70 via HAPS 10.

[0030] The relay communication station 110 mounted on the HAPS10 aircraft 100 may be a repeater-type relay communication station that relays the transmitted and received signals without regenerating them, or it may be a base station-type relay communication station that has base station equipment that regenerates the transmitted and received signals, remodulates the regenerated signals, and relays them.

[0031] The repeater-type relay station 110 functions as a repeater slave unit corresponding to a repeater master unit consisting of GW stations 70, and is, for example, a wireless relay device (hereinafter also referred to as a "frequency conversion repeater") that converts the frequency of a service link and a feeder link with a different frequency. In the downlink, the relay station 110 converts the frequency of the feeder link transmitted from the base station equipment 80 via the GW station 70 to the frequency of the service link and transmits it to the UE 61. On the other hand, in the uplink, the relay station 110 converts the frequency of the service link transmitted from the UE 61 to the frequency of the feeder link and transmits it to the base station equipment 80 via the GW station 70.

[0032] A repeater-type relay communication station 110 includes, for example, a repeater and a frequency converter. The repeater includes, for example, a low-noise amplifier that amplifies the received signal of service link SL received via the SL antenna 111, and a power amplifier that amplifies the transmitted signal of service link SL transmitted via the SL antenna 111. The frequency converter performs conversion between the frequency of service link SL and the frequency of feeder link FL.

[0033] The base station type relay station 110 has base station equipment and a frequency converter. The base station equipment includes a baseband processing unit for processing the service link baseband signal, a communication interface unit for communicating with the core network of the mobile communication network 90 via a backhaul line through the GW station 70, and the like. The frequency converter converts between the frequency of the service link signal input and output to the base station equipment within the relay station 110 and the frequency of the feeder link signal transmitted and received via the FL antenna 112.

[0034] In the embodiments described below, the case where the relay communication station 110 mounted on the HAPS10 unit 100 is a repeater-type relay communication station (repeater slave unit) will be mainly explained.

[0035] The UE (User Equipment) 61 is a terminal device used by a user on land or at sea. The UE 61 may be, for example, a mobile phone, smartphone, or portable personal computer with mobile communication capabilities, and is also called a mobile terminal, mobile station, mobile device, or portable communication terminal. The UE 61 may be a modular mobile station incorporated into a vehicle such as an automobile, or a drone such as a small, remotely controlled helicopter, or it may be a terminal device for IoT (Internet of Things) devices.

[0036] HAPS10 may autonomously control its own levitation movement (flight) and processing and control at the relay communication station 110 by having a control unit, which consists of an internally built-in computer or processor, execute a control program. For example, HAPS10 can autonomously perform the area optimization control described later. In addition, HAPS10 may acquire its own current location information (e.g., GNSS (Global Navigation Satellite System) location information such as GPS location information), pre-stored location control information (e.g., flight schedule information), location information of other HAPS located in the vicinity, and autonomously control its levitation movement (flight) and processing and control at the relay communication station 110 based on this information.

[0037] The position and attitude information of HAPS10 may be obtained based on the output of a GPS receiver, gyro sensor, accelerometer, inertial sensor, etc., incorporated into HAPS10. For example, the position and attitude information of HAPS10 may be obtained based on the output of a GNSS / INS system, which combines a GNSS system and an inertial measurement unit (IMU) incorporated into HAPS10.

[0038] Furthermore, the levitation and movement (flight) of the HAPS10, as well as the processing and control at the relay communication station 110, may be controlled by a remote control device 95 located at a communication center or the like of the mobile communication network 90. ​​The remote control device 95 can be configured, for example, as a computer device such as a PC or a server. The HAPS10 may incorporate a control communication terminal device (e.g., a mobile communication module) so that it can receive control information from the remote control device 95 and transmit various information such as monitoring information to the remote control device 95, and may be assigned terminal identification information (e.g., an IP address, a telephone number, etc.) so that it can be identified by the remote control device 95. The MAC address of the communication interface may be used to identify the control communication terminal device.

[0039] The remote control device 95 may, for example, perform area optimization control as described later by coordinating with HAPS10.

[0040] Furthermore, HAPS10 may transmit monitoring information, such as information regarding the lift-off movement (flight) of itself or surrounding HAPS and processing at the relay communication station 110, the position information of HAPS10, information regarding the status of HAPS10, and observation data acquired by various sensors, to a predetermined transmission destination such as the remote control device 95. The control information may include information on the target flight route of the HAPS. The monitoring information may include at least one piece of information such as the current position of HAPS10, flight route history information, airspeed, ground speed and thrust direction, wind speed and wind direction of the airflow around HAPS10, and atmospheric pressure and temperature around HAPS10.

[0041] The duplexing scheme for the uplink and downlink of the wireless communication between the relay station 110 and the UE61 is not limited to a specific scheme, and may be, for example, a Time Division Duplex (TDD) scheme or a Frequency Division Duplex (FDD) scheme. Furthermore, the access scheme for the wireless communication between the relay station 110 and the UE61 is not limited to a specific scheme, and may be, for example, an FDMA (Frequency Division Multiple Access) scheme, a TDMA (Time Division Multiple Access) scheme, a CDMA (Code Division Multiple Access) scheme, or an OFDMA (Orthogonal Frequency Division Multiple Access) scheme. In addition, the wireless communication may utilize MIMO (Multi-Input and Multi-Output) technology, which has functions such as diversity coding, transmit beamforming, and spatial division multiplexing (SDM), and can increase the transmission capacity per unit frequency by simultaneously using multiple antennas for both transmission and reception. Furthermore, the MIMO technology may be SU-MIMO (Single-User MIMO) technology, in which one base station transmits multiple signals to one UE at the same time and frequency, or MU-MIMO (Multi-User MIMO) technology, in which one base station transmits signals to multiple different UEs at the same time and frequency, or multiple different base stations transmit signals to one UE at the same time and frequency.

[0042] In the communication system with the above configuration, for example, signals from the base station 80 are relayed by the GW station 70 and HAPS 10, enabling communication services to be provided to the UE 61 on the ground. In particular, according to the communication system of this embodiment, the HAPS 10, which functions as an aerial relay type communication relay device acting as an aerial platform, can directly provide ultra-wide-area mobile communication services from the stratosphere at altitudes of 18 km or higher and 50 km or lower (especially around 20 km) to the UE (mobile terminal) 61 on the ground. Furthermore, the aerial platform consisting of the HAPS 10 is attracting attention as a new communication platform for use in large-scale disasters and other similar situations.

[0043] The HAPS10, as a communication platform in the air, has a very wide coverage area, and the distribution of UEs (users) 61 is not uniform. Furthermore, during large-scale disasters, different communication traffic demands arise compared to normal times. In the communication system of this embodiment, area optimization is performed to dynamically optimize the antenna parameters of the SL antenna 111 of the HAPS10 according to the UE distribution (user distribution) at any given time.

[0044] In the example of the communication system in Figure 1, area optimization is performed to optimize the antenna parameters of the SL antenna 111 so that the desired communication quality (e.g., throughput) is obtained throughout the service area 20A, which is composed of multiple cells 20C(1) to 20C(7) formed by an aerial platform such as HAPS10 facing the ground. For example, in an aerial platform such as HAPS10 that covers the service area 20A with multiple cells 20C(1) to 20C(7), dynamic area optimization control is performed to optimize the beam direction and width of each cell according to the population distribution (or user distribution, UE distribution, etc.).

[0045] In the dynamic area optimization control described above, for example, in a multi-cell configuration in which a service area 20A is composed of multiple cells 20C(1) to 20C(7), the placement of each cell is optimized so that the overall communication capacity and coverage area of ​​the service area are maximized according to the population distribution and traffic distribution. As an optimization control algorithm, for example, a genetic algorithm (GA) or a neural network (NN) can be used (see Non-Patent Documents 1 to 3 mentioned above).

[0046] For example, as shown in Figure 2(a), if multiple cells 20C(1) to 20C(3) are uniformly distributed in the service area without applying area optimization control, there is a risk that coverage and communication capacity will decrease in densely populated areas of UEs (users) 61 shown in the figure. On the other hand, in Figure 2(b), area optimization control is applied to optimize the beam direction and width for each of the multiple cells 20C(1) to 20C(3) based on big data such as the population distribution in the service area 20A. By applying area optimization control in this way, the positions of cells 20C(1) to 20C(3) are controlled to intensively cover densely populated areas of UEs (users) 61 in the service area, thereby suppressing the decrease in communication capacity in densely populated areas of UEs (users) 61. This makes it possible to maximize coverage and communication capacity in the mobile communication service area.

[0047] [Antenna parameters (beam parameters for each cell)] In area optimization control, for example, in area optimization of an area composed of multiple (N) cells, the following four types of antenna parameters A to D are defined and used as multiple types of antenna parameters for any i-th cell i within the area, and a total of 4N antenna parameters are optimized. A. Tilt angle θ tilt,i B. Vertical half width θ 3dB,i C. Horizontal half width φ 3dB,i D. Horizontal orientation of cell ω i

[0048] As shown in FIG. 3, the tilt angle θ tilt,i is the angle from the horizontal direction H of the vector Vc directed from the SL antenna 111 of HAPS10 to the center of the target i-th cell 20C(i). The vertical half-power width θ 3dB,i is the angular width between two points where the beam gain decreases by 3 dB from the maximum gain at the center of the main beam in the vertical plane P V containing the vector Vc directed to the center of the i-th cell 20C(i). The horizontal half-power width φ 3dB,i is the angular width between two points where the beam gain decreases by 3 dB from the maximum gain at the center of the main beam in the horizontal plane P H containing the vector Vc directed to the center of the i-th cell 20C(i).

[0049] Also, the horizontal directivity direction ω of the i-th cell i is the angle of the direction passing through the center of the target cell from the above reference point with respect to a predetermined reference horizontal direction Hs in the horizontal plane with the position of the SL antenna 111 of HAPS10 as the reference point.

[0050] [Problems in Dynamic Cell Control of HAPS] In general dynamic cell control of HAPS, it is possible to perform area optimization simulation with one HAPS on the premise that there are no obstacles between the HAPS and the ground (free space loss). Also, in area optimization using a drone equipped with a relay communication station, there is an example considering building penetration loss in order to cope with urban areas with many obstacles such as buildings (reference: G. Liu, H. Shakhatreh, A. Khreishah, X. Guo and N. Ansari, "Efficient Deployment of UAVs for Maximum Wireless Coverage Using Genetic Algorithm," IEEE 39th Sarnoff Symposium, Newark, NJ, USA, 2018, pp. 1-6.).

[0051] In the case of a HAPS10 located at a high altitude such as the stratosphere, as in the communication system of this embodiment, radio waves are affected by shielding and diffraction loss due to terrain such as mountains M, as shown in Figure 4. Therefore, as shown in Figure 5, radio waves from HAPS10 are affected by shielding and diffraction loss due to terrain, causing variations in the reference signal received power (RSRP) at the UE61 on the ground.

[0052] In the communication system of this embodiment, expanding coverage in areas affected by terrain requires, for example, arranging multiple HAPS10s as illustrated in Figure 6, and performing dynamic area optimization by coordinating the positions of the HAPS10s and the beams used for cell formation. However, when performing dynamic area optimization through the coordination of multiple HAPS10s, the number of combinations of positions and beam parameters (antenna parameters) of the multiple HAPS10s becomes enormous, making it difficult to find the optimal solution for area optimization.

[0053] For example, if we let "P" be the number of candidate locations for HAPS10, "H" be the number of HAPS10 units, "B" be the number of candidate beam parameter (antenna parameter) values, and "C" be the number of cell 20C units, then the total number of combinations of positions for multiple HAPS10 units and beam parameter (antenna parameter) values ​​will be enormous, as shown in equation (1) below.

number

[0054] For example, if the number of candidate locations for HAPS10 is P=1000, the number of HAPS10 units is H=10, the number of candidate values ​​for beam parameters (antenna parameters) is B=100, and the number of cells 20C is C=6, then P H =10 30 and B C×H =10 120 Therefore, the total number of combinations in equation (1) above is 10 150 It will become.

[0055] Therefore, in this embodiment, a first optimization (position optimization) that optimizes the positions of multiple HAPS10s and a second optimization (beam optimization) that optimizes the beam parameters (antenna parameters) of each of the multiple HAPS10s are performed in two stages. By performing the first optimization (position optimization) and the second optimization (beam optimization) in that order in two stages, the overall search range for area optimization for the wide-area service area 10A is reduced. The total number of combinations of search ranges when the first optimization (position optimization) and the second optimization (beam optimization) are performed in two stages is the number shown in equation (2) below.

number

[0056] For example, as mentioned above, if the number of candidate locations for HAPS10 is P=1000, the number of HAPS10 units is H=10, the number of candidate beam parameter (antenna parameter) values ​​is B=100, and the number of cells 20C is C=6, then the total number of combinations in the above equation (2) when performing area optimization in two stages is approximately 10. 120 This results in 10 combinations of the above equation (1) when the aforementioned area optimization is performed all at once. 30 It can be reduced to about one-half.

[0057] The first optimization (position optimization) described above is performed, for example, to minimize the number of HAPS10s while maximizing the area where the RSRP on the downlink at the ground UE61 is above a reference value. The second optimization (beam optimization) described above is performed to maximize the area where the SINR (signal-to-noise ratio) on the downlink at the ground UE61 is above a reference value for the positions of the multiple HAPS10s optimized in the first optimization (position optimization).

[0058] Figure 7 is a flowchart showing an example of area optimization control that takes into account geographical features, including the topography of the service area, in an area optimization device provided in a communication system according to the embodiment. In Figure 7, area optimization control S100 includes acquiring radio wave propagation characteristic data S110, area optimization of multiple HAPS S120, and application to the actual environment S130.

[0059] In the radio wave propagation characteristics data acquisition S110, for each of the multiple candidate locations in the sky where multiple HAPS10s can be placed, data on the radio wave propagation characteristics of the radio wave propagation path between the candidate location and the service area is acquired based on the geographical features of the service area (e.g., topography). For example, for all of the candidate locations for HAPS10, radio wave propagation loss data from the candidate location to each point in the service area is acquired from a model that takes the influence of topography into account (see, for example, the International Telecommunication Union Radiocommunication Sector (ITU-R) Recommendation (ITU-R Recommendation pp. 452-18, 2023)).

[0060] The area optimization S120 for multiple HAPS includes a first optimization (position optimization) S121 that optimizes the positions of multiple HAPS10, and a second optimization (beam optimization) S122 that optimizes the beam parameters (antenna parameters) for each of the multiple HAPS10 optimized in the first optimization (position optimization) S121.

[0061] In the first optimization (position optimization) S121, a search algorithm is performed for a predetermined objective function based on the radio wave propagation characteristic data (e.g., propagation loss data) for multiple candidate placement points obtained in the aforementioned radio wave propagation characteristic data acquisition S110. Examples of search algorithms that can be used include the First Fit algorithm, genetic algorithms (GA), and reinforcement learning. The First Fit algorithm is a type of algorithm used in the binning problem (the problem of minimizing the number of bins needed to pack a given load into bins (boxes, containers, etc.)), and it prioritizes filling areas starting with the largest area. The objective function for the first optimization is, for example, a function that minimizes the number of HAPS10s and maximizes the area where the RSRP of the downlink at the ground-based UE61 is equal to or greater than a reference value. Here, overlap between HAPS areas may be permitted as long as it is below a certain value.

[0062] In the second optimization (beam optimization) S122, the values ​​of antenna parameters are searched and determined using a search algorithm to adjust one or more beams from the SL antennas 111 of the multiple HAPS10 whose positions were determined in the first optimization (position optimization) S121, in order to reduce interference. For example, a genetic algorithm (GA) or reinforcement learning can be used as the search algorithm. The objective function in the second optimization is, for example, a function that maximizes the area in which the SINR of the downlink at the ground UE61 is greater than or equal to a reference value.

[0063] Furthermore, if the number of HAPS10s to be placed in the service area is large (for example, if the number of HAPS10s is greater than the reference value), the multiple HAPS10s may be divided into multiple groups, and the first optimization (position optimization) S121 and the second optimization (beam optimization) S122 described above may be performed for each group. For example, in the first optimization (position optimization) S121, the positions of the multiple HAPS10s or both the number and positions of the multiple HAPS10s are determined for each group based on radio wave propagation characteristic data (for example, propagation loss data). Also, for example, in the second optimization (beam optimization) S122 So,For each of the aforementioned groups, beam parameter values ​​are determined for the multiple HAPS10 determined in the first optimization (position optimization) S121, based on radio wave propagation characteristic data (e.g., propagation loss data). The above grouping of multiple HAPS10s may be done, for example, based on the geographical characteristics of the service area (e.g., topography) or radio wave propagation trends.

[0064] In the application to the actual environment S130, each of the multiple HAPS10 applies the optimized beam parameter (antenna parameter) settings corresponding to each of the multiple HAPS10, which were determined in the first optimization (position optimization) S121 and the second optimization (beam optimization) S122, to the formation of the cell. For example, each of the multiple HAPS10 applies the optimized antenna parameter settings corresponding to the HAPS10 to the SL antenna 111.

[0065] Figure 8 is a block diagram showing an example configuration of an area optimization device 30 provided in a communication system according to the embodiment. In Figure 8, the area optimization device 30 includes a data acquisition unit 310, a first optimization unit 320, and a second optimization unit 330.

[0066] The data acquisition unit 310 acquires data on the radio wave propagation characteristics of the radio wave propagation path between the service area 20A and each of the multiple candidate locations in the sky where multiple HAPS 10 can be placed (e.g., propagation loss data), based on the geographical features of the service area 20A (e.g., topography). The data acquisition unit 310 outputs the acquired radio wave propagation characteristics data to the first optimization unit 320. Based on the radio wave propagation characteristics data (e.g., propagation loss data) input from the data acquisition unit 310, the first optimization unit 320 determines the positions of the multiple HAPS 10 that form cells toward the service area 20A, or both the number and positions of the multiple HAPS 10. The first optimization unit 320 outputs information such as the determined positions of the HAPS 10 to the second optimization unit 330. The second optimization unit 330 determines the values ​​of the beam parameters (e.g., antenna parameters of the SL antenna 111) used to form the cell 20C for each of the multiple HAPS 10 whose number and position have been determined by the first optimization unit 320, based on the radio wave propagation characteristic data (e.g., propagation loss data) input from the data acquisition unit 310.

[0067] For example, the data acquisition unit 310 acquires radio wave propagation loss data for the radio wave propagation path between each of the multiple candidate placement points and the service area 20A, based on geographical features including the topography of the service area 20A. Here, the data acquisition unit 310 may acquire radio wave propagation characteristic data such as radio wave propagation loss data by pre-calculating it within the area optimization device (its own device) or by receiving it from an external device (for example, a server, remote control device 95, etc.).

[0068] For example, the first optimization unit 320 determines the location of multiple HAPS 10s or both the number and location of multiple HAPS 10s to maximize the area in the service area 20A where the received signal strength index value (e.g., RSRP) is equal to or greater than a reference value, based on the radio wave propagation loss data acquired by the data acquisition unit 310. Here, the radio wave propagation loss data is, for example, propagation loss data related to losses due to at least one of the blocking and diffraction of radio waves due to the terrain of the service area 20A. The received signal strength index value is the reference signal received power (RSRP) of the UE 61 in the service area 20A.

[0069] For example, the second optimization unit 330 determines, for each of the multiple HAPS 10 whose positions or both are determined by the first optimization unit 320, the values ​​of the beam parameters (e.g., antenna parameters of the SL antenna 111) used to form the cell 20C so as to maximize the area in the service area 20A where the received signal strength index value (RSRP) is equal to or greater than a reference value.

[0070] Furthermore, if the multiple HAPS10s are divided into multiple groups, the first optimization unit 320 and the second optimization unit 330 may perform optimization for each group. For example, the first optimization unit 320 may determine the position of the multiple HAPS10s or both the number and position of the multiple HAPS10s for each group, in this case, the first optimization unit 320 for each group, based on radio wave propagation characteristic data (e.g., radio wave propagation loss data). Alternatively, the second optimization unit 330 may determine the beam parameter values ​​(e.g., antenna parameters of the SL antenna 111) for the multiple HAPS10s after the position or both the number and position have been determined by the first optimization unit 320, based on the radio wave propagation characteristic data (e.g., radio wave propagation loss data) for each group.

[0071] The communication system of this embodiment may also include an area optimization device 30 and a plurality of HAPS 10 whose location or number and position have been determined by the area optimization device 30. Each of the plurality of HAPS 10 applies the set values ​​of beam parameters (for example, antenna parameters of the SL antenna 111) corresponding to the HAPS 10, which have been determined by the second optimization unit 330 of the area optimization device 30, to the formation of cells.

[0072] Furthermore, the area optimization device 30 shown in Figure 8 may be installed on any one of the multiple HAPS 10s. In this case, the HAPS 10 on which the area optimization device 30 is installed will form cells 20C using the values ​​of the beam parameters (for example, the antenna parameters of the SL antenna 111) corresponding to that HAPS (itself) 10 after optimization by the area optimization device 30. The area optimization device 30 also includes a transmitting unit 35 that transmits the values ​​of the beam parameters (for example, the antenna parameters of the SL antenna 111) corresponding to the other HAPS 10 after optimization to those other HAPS 10s. Those other HAPS 10s will form cells 20C using the values ​​of the optimized beam parameters (for example, the antenna parameters of the SL antenna 111) received from the HAPS 10 on which the area optimization device 30 is installed.

[0073] Alternatively, the area optimization device 30 shown in Figure 8 may be provided on a remote control device 95 capable of communicating with each of the multiple HAPS 10s. In this case, the remote control device 95 equipped with the area optimization device 30 includes a transmitting unit 35 that transmits the values ​​of the optimized beam parameters (for example, the antenna parameters of the SL antenna 111) corresponding to each of the multiple HAPS 10s. Each HAPS 10 uses the values ​​of the optimized beam parameters (for example, the antenna parameters of the SL antenna 111) received from the remote control device 95 to form cells 20C.

[0074] In this embodiment, the acquisition of radio wave propagation characteristic data in the area optimization device 30, and the area optimization control including the first optimization (position optimization) and second optimization (beam optimization) S122, may be performed at any time. For example, area optimization control may be performed during system design before the start of operation of the communication system, when the start of operation of the communication system, at periodic intervals after the start of operation of the communication system, or when the configuration of the SL antenna 111 of any of the HAPS 10 is changed. Furthermore, in this embodiment, the area optimization control may be performed when the geographical features of the service area 20A, such as the topography, change, or when the desired communication quality (e.g., throughput) deteriorates across the entire service area 20A.

[0075] As described above, this embodiment makes it possible to optimize coverage in a wide service area 20A where radio wave blocking and diffraction losses occur due to terrain effects. Moreover, since this optimization is divided into two stages—a first optimization concerning the location of the aerial PF or both the number and location of the aerial PFs, and a second optimization concerning the antenna parameters for beamforming in the aerial PFs—the computational load for optimizing the service area 20A can be reduced.

[0076] Furthermore, the present invention enables the construction of a new communication platform for use in large-scale disasters, etc., that can provide ultra-wide-area mobile communication services from the stratosphere at an altitude of about 20 km to terminal devices on the ground, thus contributing to the achievement of Sustainable Development Goal (SDG) 9, "Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation."

[0077] The processing steps and components of the aerial PFs such as HAPS and remote control devices described herein can be implemented by various means. For example, these steps and components may be implemented using hardware, firmware, software, or a combination thereof.

[0078] With respect to hardware implementation, means such as processing units used to realize the above processes and components in a physical entity (e.g., various wireless communication devices, Node B, terminals, hard disk drive devices, or optical disc drive devices) may be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, computers, or combinations thereof.

[0079] Furthermore, with respect to the firmware and / or software implementation, means such as processing units used to realize the above-mentioned components may be implemented in the form of a program (e.g., code such as procedures, functions, modules, instructions, etc.) that performs the functions described herein. Generally, any computer / processor-readable medium that clearly embodies the firmware and / or software code may be used to implement means such as processing units used to realize the above-mentioned processes and components as described herein. For example, the firmware and / or software code may be stored in memory in a control device, for example, and executed by a computer or processor. That memory may be implemented inside the computer or processor, or it may be implemented outside the processor. Also, the firmware and / or software code may be stored in a computer or processor-readable medium such as random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), electrically erasable PROM (EEPROM), flash memory, floppy disks, compact disks (CDs), digital versatile disks (DVDs), magnetic or optical data storage devices, etc. The code may be executed by one or more computers or processors, and the computers or processors may be made to perform functional embodiments as described herein.

[0080] Furthermore, the medium may be a non-temporary recording medium. Also, the program code may be readable and executable by a computer, processor, or other device or machine, and its format is not limited to a specific format. For example, the program code may be source code, object code, or binary code, or it may be a mixture of two or more of these codes.

[0081] Furthermore, the descriptions of embodiments disclosed herein are provided to enable those skilled in the art to manufacture or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the general principles defined herein are applicable to other variations without departing from the spirit or scope of the disclosure. Therefore, the disclosure is not limited to the examples and designs described herein, but should be accepted in the broadest sense that conforms to the principles and novel features disclosed herein. [Explanation of symbols]

[0082] 10:HAPS(Upper air PF) 20A: Service Area 20C: Cell 20F: Footprint 30: Area Optimization Device 35: Transmitter 61: UE (Terminal Device) 70: GW Station 71: Wireless relay device 80:Base station equipment 90: Mobile communication network (core network) 95: Remote control device 100: Aircraft 110: Relay communication station 111: Service link antenna (SL antenna) 310: Data acquisition unit 320: First Optimization Unit 330: Second Optimization Department

Claims

1. An area optimization device for optimizing the service area of ​​mobile communications by multiple aerial PFs (platforms) equipped with relay communication station antennas capable of beamforming control to form one or more cells toward the ground, A data acquisition unit acquires data on the radio wave propagation characteristics of the radio wave propagation path between the candidate location and the service area, based on the geographical characteristics of the service area, for each of the multiple candidate locations in the air where the multiple air PFs can be placed. A first optimization unit determines, based on the data of radio wave propagation characteristics, the positions of the multiple aerial PFs that form the cells toward the service area, or both the number and positions of the multiple aerial PFs. A second optimization unit determines the beam parameter values ​​used to form the cell for each of the multiple upper-air PFs after the first optimization unit has determined the position or both the number and position, based on the radio wave propagation characteristics data. An area optimization device characterized by comprising the following features.

2. In the area optimization apparatus of claim 1, The data acquisition unit acquires radio wave propagation loss data for the radio wave propagation path between each of the plurality of candidate placement points and the service area, based on geographical features including the topography of the service area. The first optimization unit determines, based on the radio wave propagation loss data, the position of the plurality of aerial PFs or both the number and position of the plurality of aerial PFs to maximize the area in the service area where the received intensity index value is equal to or greater than a reference value. The second optimization unit determines, for each of the multiple upper-air PFs after the first optimization unit has determined the position or both the number and position, the values ​​of the beam parameters used to form the cell so as to maximize the area in the service area where the received intensity index value is equal to or greater than a reference value. An area optimization device characterized by the following features.

3. In the area optimization apparatus of claim 2, The aforementioned radio wave propagation loss data is propagation loss data relating to losses caused by at least one of the blocking and diffraction of radio waves due to the topography of the service area. The aforementioned received signal strength index value is the reference signal received power (RSRP) of the terminal device in the service area. An area optimization device characterized by the following features.

4. In the area optimization apparatus of claim 1, The aforementioned multiple aerial PFs are divided into multiple groups, The first optimization unit determines, for each group, the positions of the multiple upper-air PFs that form the cell, or both the number and positions of the multiple upper-air PFs, based on the data of the radio wave propagation characteristics. The second optimization unit determines the beam parameter values ​​for each group of upper-air PFs after the first optimization unit has determined the position or both the number and position, based on the data of the radio wave propagation characteristics. An area optimization device characterized by the following features.

5. In the area optimization apparatus of claim 1, The data acquisition unit acquires the radio wave propagation characteristics data by pre-calculating it within the device or by receiving it from an external device. An area optimization device characterized by the following features.

6. An area optimization device according to any one of claims 1 to 5, The area optimization device comprises a plurality of aerial PFs whose positions or the number and positions are determined by the area optimization device, Each of the aforementioned plurality of upper air PFs applies the beam parameter setting value corresponding to the upper air PF determined by the second optimization unit of the area optimization device to the formation of the cell. A system characterized by the following features.

7. In the system of claim 6, The area optimization device is installed in one of the multiple upper air PFs, Any one of the above-mentioned upper-air PFs includes a transmitting unit that transmits the beam parameter setting values ​​corresponding to the other upper-air PFs among the plurality of upper-air PFs to the other upper-air PFs, A system characterized by comprising:

8. In the system of claim 6, The system further includes a remote control device capable of communicating with each of the aforementioned multiple aerial PFs, The remote control device is The area optimization device and, The system includes a transmitting unit that transmits the set value of the beam parameter corresponding to each of the plurality of upper air PFs to each of the upper air PFs, A system characterized by the following features.

9. A remote control device capable of communicating with each of a plurality of aerial PFs (platforms) equipped with relay communication station antennas that are beamforming controllable to form one or more cells toward the ground, An area optimization device according to any one of claims 1 to 5, A transmitting unit that transmits the set value of the beam parameter corresponding to the upper air PF to each of the plurality of upper air PFs that form the cell toward the service area, A remote control device characterized by comprising:

10. An optimization method for optimizing the service area of ​​mobile communications by multiple aerial PFs (platforms) equipped with beamforming controllable relay station antennas to form one or more cells toward the ground, For each of the multiple candidate locations in the air where the multiple aerial PFs can be placed, data on the radio wave propagation characteristics of the radio wave propagation path between the candidate location and the service area is obtained based on the geographical characteristics of the service area. Based on the data of the radio wave propagation characteristics, a first optimization is performed to determine the positions of the multiple aerial PFs that form the cells toward the service area, or both the number and positions of the multiple aerial PFs. Based on the data of the radio wave propagation characteristics, a second optimization is performed to determine the values ​​of the beam parameters used to form the cells for each of the multiple upper-air PFs after the position or both the number and position have been determined in the first optimization. An optimization method characterized by including

11. A program executed on a computer or processor installed in an area optimization device that optimizes the service area of ​​mobile communications by multiple aerial PFs (platforms) equipped with beamforming controllable relay station antennas to form one or more cells toward the ground, A program code for acquiring data on the radio wave propagation characteristics of the radio wave propagation path between the candidate location and the service area, based on the geographical characteristics of the service area, for each of the multiple candidate locations in the air where the multiple air PFs can be placed. A program code for determining, based on the data of radio wave propagation characteristics, the positions of a plurality of aerial PFs that form the cell toward the service area, or both the number and positions of the plurality of aerial PFs, A program code for determining the values ​​of beam parameters used to form the cell for each of the multiple upper-air PFs after determining the position or both the number and position based on the radio wave propagation characteristics data, A program characterized by including the following:

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