Control device and control method

Abstract

To provide a control device, a communication system, and a control method that can simply control parameters related to wireless communication according to changes in a wireless communication environment.SOLUTION: A control device includes: an acquisition unit that acquires, for each terminal, a reception result indicating a result of reception processing for a signal transmitted from each of a plurality of terminals; and a control unit that centrally controls the plurality of terminals, and based on the reception results, performs machine learning common to the plurality of terminals, and determines a parameter related to wireless communication used by each of the plurality of terminals.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to a control device , and The present invention also relates to a control method. [Background technology]

[0002] A band that does not require a license (unlicensed band) may be used for communication between wireless communication devices (for example, between a base station and a terminal). Since the unlicensed band is used by various wireless systems, various changes in the wireless communication environment including interference occur.

[0003] For example, Patent Document 1 describes a wireless communication system that, when allocating channels to be used for communication to a plurality of base stations, determines channel allocation so as to minimize the amount of interference. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2013-81089 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, there is room for further study on a method for controlling parameters relating to wireless communication, such as channels used by terminals, in response to changes in the wireless communication environment.

[0006] Non-limiting examples of the present disclosure contribute to providing a control device, a communication system, and a control method that can easily control parameters related to wireless communication in response to changes in the wireless communication environment. [Means for solving the problem]

[0007] A control device according to one embodiment of the present disclosure includes an acquisition unit that acquires, for each of a plurality of terminals, a reception result indicating the result of reception processing for a signal transmitted from the respective terminal, and a control unit that centrally controls the plurality of terminals, and performs machine learning common to the plurality of terminals based on the reception result, and determines parameters related to wireless communication used by each of the plurality of terminals.

[0008] A communication system according to one embodiment of the present disclosure includes a plurality of terminals and a control device that centrally controls the plurality of terminals, the control device including an acquisition unit that acquires, for each of the plurality of terminals, a reception result indicating a result of reception processing for a first signal transmitted from each of the plurality of terminals, and a first control unit that performs machine learning common to the plurality of terminals based on the reception result and determines parameters related to wireless communication to be used by each of the plurality of terminals, and the terminal includes a receiving unit that receives control information including the parameters from the control device, a second control unit that performs transmission processing of a second signal using the parameters, and a transmitting unit that transmits the second signal.

[0009] In a control method according to one embodiment of the present disclosure, a control device that centrally controls multiple terminals acquires, for each of the multiple terminals, reception results indicating the results of reception processing for signals transmitted from each of the multiple terminals, and performs machine learning common to the multiple terminals based on the reception results, thereby determining parameters related to wireless communication to be used by each of the multiple terminals.

[0010] In addition, these comprehensive or specific aspects may be realized by a system, an apparatus, a method, an integrated circuit, a computer program, or a recording medium, or may be realized by any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. Effect of the Invention

[0011] According to an embodiment of the present disclosure, parameters related to wireless communication can be easily controlled in response to changes in the wireless communication environment.

[0012] Further advantages and benefits of an embodiment of the present disclosure will become apparent from the specification and drawings, in which such advantages and / or benefits are provided by some of the embodiments and features described in the specification and drawings, respectively, but not necessarily all of which are provided to obtain one or more identical features. [Brief description of the drawings]

[0013] [Figure 1] Diagram showing an overview of wireless systems including LPWA [Diagram 2] FIG. 1 is a block diagram illustrating an example of a network configuration according to an embodiment of the present disclosure. [Diagram 3] FIG. 1 is a block diagram showing a configuration example of a base station according to an embodiment of the present disclosure. [Figure 4] FIG. 1 is a block diagram showing a configuration example of a centralized control server according to an embodiment of the present disclosure. [Diagram 5] FIG. 1 is a block diagram illustrating a configuration example of a terminal according to an embodiment of the present disclosure. [Figure 6] A diagram showing an example of a reinforcement learning model [Figure 7] A diagram showing an example of a multi-agent model [Figure 8] A diagram showing an example of a model in which a learning device is provided for each agent. [Figure 9] A diagram showing an example of a model in which a common learning module is provided between agents. [Figure 10] FIG. 1 is a diagram showing an example of a sequence of processing steps according to an embodiment of the present disclosure. [Figure 11] A diagram showing an example of a model including a learner in variation 1. [Figure 12] A diagram showing an example of a model including a learner in variation 2. [Figure 13] A diagram showing an example of a model for information exchange in variation 2. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functions are denoted by the same reference numerals, and redundant description will be omitted.

[0015] (One embodiment) In unlicensed bands (for example, frequency bands such as the 920 MHz band, the 2.4 GHz band, and the 5 GHz band), in addition to wireless LAN (Local Area Network) communications, communications are also carried out by IoT (Internet of Things) terminals and / or M2M (Machine to Machine) terminals.

[0016] For example, in the IoT and / or M2M, use of a wireless communication technology called Low Power Wide Area (LPWA), which enables communication over a wide area with low power consumption, is being considered.

[0017] There are multiple methods (standards or RATs (Radio Access Technologies)) for LPWA. For example, LPWA communication methods include a first communication method that uses a spread spectrum method for communication and a second communication method that does not use a spread spectrum method. The first communication method includes, for example, a communication method called "LoRa." The second communication method includes, for example, a communication method called "Wi-SUN (Wireless Smart Utility Network)."

[0018] Terminals that support communication in an LPWA system (hereinafter, sometimes referred to as "LPWA terminals") are not limited to terminals owned by users, but are installed in various devices. For example, LPWA terminals are installed in home appliances such as televisions, air conditioners, washing machines, and refrigerators, as well as in mobile transportation such as vehicles.

[0019] In addition to LPWA, unlicensed bands are used by a variety of systems, including Wi-fi (registered trademark) and RFID (Radio Frequency IDentifier), resulting in a rapid increase in traffic and interference.

[0020] Therefore, for example, in an LPWA system, it is desirable that parameters (eg, channels) used for communication between LPWA terminals be appropriately determined in consideration of interference and the like.

[0021] FIG. 1 is a diagram showing an overview of a wireless system including an LPWA system.

[0022] 1 shows group #1, group #2, and group #3. Each group includes multiple devices.

[0023] Both groups #1 and #2 are LPWA systems. However, network #1 (NW#1) to which each device in group #1 belongs is different from network #2 (NW#2) to which each device in group #2 belongs. For example, NW#1 and NW#2 are the same LPWA system, but are networks operated by different operators. The LPWA system in group #2 is an LPWA system in a network (unmanaged network) not managed by group #1.

[0024] Group #1 includes devices that belong to NW #1 and are connected to NW #1 by wire or wirelessly. For example, group #1 includes gateway #1 (GW #1), GW #2, and terminals #1 to #3 of an LPWA system. Group #1 also includes centralized control server #1 that centrally controls the GWs and the like via NW #1.

[0025] Group #2 includes devices that belong to NW #2 and are connected to NW #2 by wire or wirelessly. For example, group #2 includes GW #3 and terminals #4 to #5 of an LPWA system. Group #2 also includes centralized control server #2 that centrally controls the GWs and the like via NW #2.

[0026] Note that the number of devices in group #1 and group #2 in FIG. 1 is an example, and the present disclosure is not limited thereto. For example, the number of GWs included in one group may be three or more. Also, the number of terminals included in one group may be one, or four or more.

[0027] In addition, other devices may be connected to the NWs of each group. For example, group #1 may include a relay station that relays wireless communication between GW #1 and / or GW #2 and terminals #1 to #3. Group #2 may also include a similar relay station.

[0028] Group #3 is a wireless system different from the wireless system (LPWA system) of group #1. The wireless system of group #3 is a wireless system of an unmanaged network not managed by group #1. The wireless system of group #3 is, for example, RFID and Wi-fi. Group #3 includes RFID readers / writers and RFID tags, and terminals using Wi-fi. The wireless system of group #3 may include LTE (Long Term Evolution) systems and radar systems. Furthermore, group #3 may include noise sources other than wireless systems, such as general home appliances, lighting equipment, heavy machinery equipment, etc.

[0029] Note that the network configuration and / or device configuration shown in FIG. 1 is an example, and the present disclosure is not limited thereto.

[0030] In addition, the above-mentioned GW may have a function of an interference monitoring device that measures interference. In the following description, a "base station" corresponds to a GW having the function of an interference monitoring device. "Interference monitoring" may be replaced with other notations such as "radio wave monitoring" and "communication environment monitoring."

[0031] Furthermore, each network shown in Fig. 1 may include a device other than the device shown in Fig. 1. In that case, the other device may have some or all of the functions of the device shown in Fig. 1. For example, if a relay station is provided in group #1 or group #2, the relay station may have the function of an interference monitoring device. Furthermore, the relay station may have the function of a GW and an interference monitoring function. Alternatively, the relay station may have the function of an interference monitoring device and not have the function of a GW.

[0032] Each of the wireless devices in groups #1 to #3 uses a common system band (e.g., an unlicensed band). Therefore, each of the wireless devices in groups #1 to #3 is subject to interference from the other wireless devices. The following describes the interference that the wireless devices in group #1 are subject to as an example.

[0033] For example, a signal transmitted by a first wireless device (e.g., terminal #2) included in group #1 to a second wireless device (e.g., GW #1) included in group #1 may also be received (detected) by a third wireless device (e.g., GW #2) included in group #1. In this case, the third wireless device may cause interference due to the signal. In the following, an interference signal received by a wireless device belonging to NW #1 from another wireless device belonging to NW #1 may be referred to as a "signal within management". For example, a signal within management corresponds to interference received by a wireless device belonging to NW #1 that supports communication of an LPWA system from another wireless device belonging to NW #1 that supports communication of the LPWA system.

[0034] Furthermore, for example, a signal transmitted by a wireless device (e.g., terminal #5 and / or an RFID reader / writer) included in group #2 and / or group #3 causes interference in a wireless device (e.g., terminal #1) included in group #1. Hereinafter, interference received by a wireless device belonging to NW #1 from a wireless device not belonging to NW #1 may be described as "unmanaged interference". For example, unmanaged interference corresponds to interference received by a wireless device that supports communication of an LPWA system and belongs to NW #1 from a wireless device not belonging to NW #1. Alternatively, unmanaged interference corresponds to interference components excluding within-management signals from among detected signals (interference).

[0035] Uncontrolled interference may be further classified based on the cause of the interference.

[0036] For example, a signal transmitted by a wireless device (e.g., terminal #4) included in group #2 causes interference in a wireless device (e.g., GW #1) included in group #1. Hereinafter, interference received by a wireless device belonging to NW #1 from a wireless device belonging to NW #2 may be referred to as "radio interference" among "unmanaged interference". For example, "radio interference" corresponds to interference received by a wireless device belonging to NW #1, which supports LPWA system communication, from a wireless device belonging to NW #2, which supports LPWA system communication and is different from NW #1.

[0037] Also, for example, a signal transmitted by a wireless device (e.g., an RFID reader / writer) included in group #3 causes interference in a wireless device (e.g., GW#1) included in group #1. Hereinafter, interference received by a wireless device that supports LPWA system communications and belongs to NW#1 from a wireless device that supports a wireless system different from the LPWA system may be referred to as "environmental noise" of "unmanaged interference."

[0038] As shown in Fig. 1 as an example, an LPWA system uses a common system band with a different wireless system from the LPWA system and / or with the same LPWA system belonging to a different network. In such a situation, the wireless communication environment changes depending on the difference in time and / or space, and appropriate wireless communication control according to the environment is desired.

[0039] A wireless communication control based on a general rule (which may be referred to as a "rule-based wireless communication control") may be applicable in a limited wireless communication environment (e.g., the size of a communication area and / or the number of terminals, etc.), but may not be applicable when the range of the limited wireless communication environment is exceeded. Alternatively, the rules and / or parameters may need to be adjusted for each wireless communication environment.

[0040] Furthermore, when a rule is designed that can be applied to a wider range of wireless communication environments, the designed rule may become complicated due to an increase in the number of parameters, the number of processing steps based on the rule, etc.

[0041] Furthermore, even if rules are designed that can be applied to a wider range of wireless communication environments, the designed rules will need to be reviewed and adjusted in response to changes in the wireless communication environment (e.g., an increase in the number of communication areas due to the installation of new base stations).

[0042] As described above, in wireless communication control based on general rules, it is costly to design and develop the rules, and even when control is based on the designed rules, it is costly to operate the control.

[0043] Non-limiting examples of the present disclosure describe how reinforcement learning, an example of machine learning, can be used to achieve control (e.g., parameter control) adapted to a wireless communication environment without designing complex rules and adjusting parameters.

[0044] <Network configuration example> Fig. 2 is a block diagram showing a configuration example of a network (NW) according to this embodiment. The network shown in Fig. 2 includes base stations 10 (base stations 10-1 to 10-L (L is an integer equal to or greater than 1)), a centralized control server 20, and terminals 30-1 to 30-M (hereinafter, may be simply referred to as terminals #1 to #M (M is an integer equal to or greater than 1)). Each device included in the network shown in Fig. 2 corresponds to the device of group #1 shown in Fig. 1, and supports, for example, communication of an LPWA system.

[0045] The base station 10 wirelessly connects to a terminal 30 (any of terminals #1 to #M) and performs wireless communication on a channel assigned to the terminal. The base station 10 also performs interference monitoring on each of the available channels and outputs the interference classification result to the central control server 20.

[0046] The centralized control server 20 is connected to the base station 10 by wired connection and acquires the classification result from the base station 10. The centralized control server 20 may also acquire information on terminals wirelessly connected to the base station 10 from the base station 10. The centralized control server 20 determines channels to be assigned to the terminals in the base station 10 based on the classification result. The centralized control server 20 outputs assignment information including information on the channels to be assigned to the terminals to the base station 10.

[0047] Terminals #1 to #M are each an LPWA terminal that communicates with base station 10 (any of base stations 10-1 to 10-L) in the LPWA system.

[0048] <Base station configuration example> 3 is a block diagram showing an example of the configuration of the base station 10 according to the present embodiment. The base station 10 corresponds to, for example, GW#1 or GW#2 belonging to the NW#1 shown in FIG.

[0049] The base station 10 includes a receiving unit 101 , a demodulating / decoding unit 102 , an interference classification unit 103 , a control unit 104 , a control signal generating unit 105 , an encoding / modulating unit 106 , and a transmitting unit 107 .

[0050] The receiving unit 101 receives a signal transmitted by a terminal and performs a predetermined receiving process on the received signal. For example, the predetermined receiving process includes a frequency conversion process (down-conversion) based on the frequency of a channel assigned to the terminal or the frequency of a channel for transmitting a control signal. Information on the frequency of the channel assigned to the terminal may be acquired from the control unit 104, for example.

[0051] Furthermore, the receiver 101 receives (detects) signals in each available channel (e.g., each channel included in an unlicensed band) in the system band for interference measurement (e.g., radio wave monitoring). Then, the receiver 101 performs a predetermined reception process on the received signal. The predetermined reception process includes, for example, a frequency conversion process based on the frequency of each channel. Each available channel in the system band may correspond to a candidate channel that can be assigned to the terminal 30.

[0052] The receiving unit 101 outputs a received signal that has been subjected to predetermined reception processing to a demodulation / decoding unit 102 and an interference classification unit 103 .

[0053] The demodulation / decoding unit 102 performs demodulation and decoding on the received signal obtained from the receiving unit 101, generates received data, and outputs it to the control unit 104. The received data may include an identifier for identifying a terminal that belongs to the same NW (NW#1) as the base station 10. The demodulation / decoding unit 102 may output information indicating whether or not the received signal has been successfully received to the control unit 104. For example, the demodulation / decoding unit 102 may determine that the received signal has been successfully received if it has been able to generate received data or if there is no error in the received data.

[0054] The interference classification unit 103 performs, for example, radio wave monitoring. For example, the interference classification unit 103 detects interference in each channel and classifies the detected interference. For example, the interference classification unit 103 monitors a received signal in one channel for a predetermined period of time and classifies the received signal into the above-mentioned in-management signal and out-of-management interference.

[0055] For example, the interference classification unit 103 detects a preamble of a received signal. A signal transmitted by a terminal supporting an LPWA system is provided with a preamble of the LPWA system. For example, the interference classification unit 103 calculates a correlation between a preamble used in the LPWA system and a received signal. The preamble used in the LPWA system may be common regardless of the network to which the terminal that is the transmission source of the received signal belongs.

[0056] If the correlation between the preamble and the received signal does not produce a peak equal to or greater than a predetermined value, the interference classification unit 103 determines that the source of the received signal is not an LPWA terminal. In this case, the interference classification unit 103 determines that the source of the received signal is a wireless device that supports a wireless system different from the LPWA system, and that the received signal corresponds to environmental noise, which is an example of unmanaged interference.

[0057] For example, when a peak equal to or greater than a predetermined value occurs as a result of correlation between the preamble and the received signal, the interference classification unit 103 determines that the transmission source of the received signal is an LPWA terminal.

[0058] Here, the preamble used in the communication of the LPWA system may be common regardless of the network to which the terminal that is the transmission source of the received signal belongs. Therefore, when the interference classification unit 103 determines that the transmission source of the received signal is an LPWA terminal, it determines whether the network to which the transmission source belongs is the same network (NW#1) as the base station 10 or a different network (for example, NW#2 in FIG. 1) from the base station 10.

[0059] For example, the interference classification unit 103 determines the NW to which the transmission source belongs based on the decoding result of the received signal obtained from the demodulation / decoding unit 102. For example, if the received signal is correctly decoded and contains an identifier, the interference classification unit 103 determines that the NW to which the transmission source of the received signal belongs is the same NW as the base station 10. On the other hand, for example, if the received signal is not correctly decoded and does not contain an identifier, the interference classification unit 103 determines that the NW to which the transmission source of the received signal belongs is a NW different from the base station 10.

[0060] The interference classification unit 103 determines that the received signal corresponds to an in-management signal when the source of the received signal is an LPWA terminal that belongs to the same NW#1 as the base station 10. The interference classification unit 103 determines that the received signal corresponds to radio interference, which is an example of unmanaged interference, when the source of the received signal is an LPWA terminal that belongs to a NW different from the base station 10.

[0061] The classification method in the interference classification unit 103 is not limited to the above-mentioned method based on the preamble detection result of the received signal and the decoding result of the received signal.

[0062] For example, the interference classification unit 103 may classify the received signal into within-management signals and interference different from within-management signals (unmanaged interference). In this case, the interference classification unit 103 does not need to classify the unmanaged interference into radio interference and environmental noise. For example, the interference classification unit 103 may classify within-management signals from the received signals based on the decoding result of the received signals, and detect the unmanaged interference by subtracting the within-management signals from the received signals. Also, the interference classification unit 103 may determine the amount of interference of the received signal without classifying the received signal into within-management signals and unmanaged interference.

[0063] The interference classification unit 103 determines the channel occupancy rate (channel usage rate) and reception level of each channel from the amount of interference.

[0064] The interference classification unit 103 performs radio wave monitoring and outputs information indicating the result of the radio wave monitoring to the control unit 104. For example, the information output to the control unit 104 may include the channel occupancy rate (channel usage rate) and reception level of each of the above-mentioned channels.

[0065] The way of expressing the amount of interference is not particularly limited. For example, the amount of interference may be expressed by the average value, minimum value, or maximum value of the received signal power (which may be called interference power). Alternatively, the amount of interference may be expressed using the relationship between the received signal power and the time interval during which the received signal is received (which may be called monitoring interval). For example, the amount of interference may be expressed by a time interval during which the received signal power has a value equal to or greater than a predetermined value, or by whether or not the time interval during which the received signal power has a value equal to or greater than a predetermined value is longer than a predetermined length.

[0066] The control unit 104 generates information to be output to the centralized control server 20. For example, the control unit 104 outputs information (for example, a reception result, etc.) indicating at least one of whether reception of a reception signal was successful, a reception success rate, and a reception success time interval to the centralized control server 20. For example, the control unit 104 may calculate the reception success rate and / or the reception success time interval based on information indicating whether reception of a reception signal was successful at each of a plurality of reception timings.

[0067] Furthermore, the control unit 104 outputs information such as the channel occupancy rate (channel usage rate) and reception level of each channel to the centralized control server 20 of NW#1 (see Figs. 1 and 2). The information output from the control unit 104 to the centralized control server 20 may be referred to as a reception result indicating the result of reception processing in the base station 10. Note that the reception processing in the base station 10 may include processing of signals transmitted from the terminal 30 to the base station 10, and processing of signals obtained by monitoring each of the candidate channels.

[0068] The control unit 104 may perform a conversion process on the information to be output to the centralized control server 20, and output the information after the conversion process to the centralized control server 20.

[0069] The control unit 104 acquires information about parameters set in the terminal 30 from the central control server 20 of the NW#1 (see FIGS. 1 and 2).

[0070] The control unit 104 outputs information relating to the parameters to the control signal generating unit 105 .

[0071] The control unit 104 also controls data communication with the terminal. For example, the received data acquired from the demodulation / decoding unit 102 may be output to an external network (not shown) or other device in the NW#1. The control unit 104 also outputs transmission data addressed to the terminal 30 acquired from an external network or other device in the NW#1 to the encoding / modulation unit 106.

[0072] The control signal generating unit 105 generates a control signal including control information addressed to the terminal, based on the information acquired from the control unit 104. The control signal generating unit 105 outputs the control signal to the encoding / modulating unit .

[0073] The coding / modulation unit 106 performs coding and modulation processes on the transmission data acquired from the control unit 104 to generate a transmission signal. The coding / modulation unit 106 also performs coding and modulation processes on the control signal acquired from the control signal generation unit 105 to generate a transmission control signal. The coding / modulation unit 106 outputs the transmission signal and / or the transmission control signal to the transmission unit 107.

[0074] The transmitting unit 107 performs a predetermined transmission process on the transmission signal. For example, the predetermined transmission process includes a frequency conversion process (up-conversion) based on the frequency of the channel assigned to the terminal 30. Information on the frequency of the channel assigned to the terminal 30 may be acquired from the control unit 104, for example.

[0075] Furthermore, the transmitting unit 107 performs a predetermined transmission process on the transmission control signal. For example, the predetermined transmission process includes a frequency conversion process (up-conversion) based on the frequency of a channel for transmitting the transmission control signal to the terminal 30. The channel for transmitting the transmission control signal to the terminal 30 may be, for example, a predetermined channel, or may be a channel currently being used for communication with the terminal 30.

[0076] <Example of centralized control server configuration> Fig. 4 is a block diagram showing a configuration example of the centralized control server 20 according to this embodiment. The centralized control server 20 belongs to, for example, NW#1 shown in Fig. 1. For example, the centralized control server 20 is connected to the above-mentioned base station 10 by wire. Alternatively, the centralized control server 20 may be connected to a network such as the Internet by wire and connected to the base station 10 via the network.

[0077] The centralized control server 20 includes a receiving unit 201 , a control unit 202 , and a transmitting unit 203 .

[0078] The receiving unit 201 receives information from, for example, the base station 10. For example, the information received from the base station 10 includes a reception result indicating a result of a reception process in the base station 10. The reception result includes information indicating at least one of whether reception was successful, a reception success rate, and a reception success time interval. The reception result may also include at least one of a channel usage rate of each channel and a reception level of each channel.

[0079] The control unit 202 selects (determines) parameters to be set for each terminal 30 based on the information received from the base station 10. For example, the control unit 202 performs a learning process based on the notification result and selects (determines) a channel to be assigned to the terminal 30.

[0080] The learning process in the control unit 202 may be executed by a learning device (not shown) included in the control unit 202, for example.

[0081] The transmitting unit 203 transmits information including the parameters of each terminal 30 set in the control unit 202 to the base station 10 .

[0082] In the above description, an example has been described in which the configuration shown in FIG. 3 is included in one base station 10, and the configuration shown in FIG. 4 is included in one centralized control server 20. The present disclosure is not limited to this. For example, the base station 10 may have at least a part of the configuration of the centralized control server 20, or the centralized control server 20 may have at least a part of the configuration of the base station 10. For example, in the network shown in FIG. 2, at least one of the base stations 10 may have the configuration of the centralized control server 20.

[0083] For example, the configuration of the base station 10 shown in FIG. 3 may be divided into a first device having a communication function of the LPWA system and a second device having a function of a radio interference monitoring device (for example, an interference classification unit 103).

[0084] <Example of terminal configuration> 5 is a block diagram showing an example of the configuration of the terminal 30 according to the present embodiment. The terminal 30 includes a receiving unit 301, a control unit 302, and a transmitting unit 303.

[0085] The receiver 301 receives a signal from the base station 10, for example, via an antenna. For example, the signal received from the base station 10 is a signal including downlink data and a signal including control information. The receiver 301 performs reception processing on the received signal and outputs the downlink data and / or the control information to the controller 302.

[0086] The control unit 302 processes downlink data and outputs the data to a processing unit of a higher layer (not shown). The control unit 302 outputs the uplink data acquired from the processing unit of the higher layer to the transmission unit 303.

[0087] The control unit 302 sets parameters related to wireless communication based on the downlink control information. For example, the control unit 302 sets a channel to be used for signal transmission processing based on channel information included in the control information. The control unit 302 also sets other parameters (e.g., spreading factor and transmission power) included in the control information as parameters to be used for signal transmission processing. The control unit 302 also generates uplink control information and outputs it to the transmission unit 303.

[0088] The transmitter 303 performs transmission processing of uplink data and / or control information, and generates a transmission signal. The transmitter 303 transmits the transmission signal via an antenna.

[0089] The control unit 302 may set parameters to be used in signal reception processing based on the control information.

[0090] <Reinforcement learning> Next, reinforcement learning will be described as an example of machine learning executed by the control unit 202 of the central control server 20. Fig. 6 is a diagram showing an example of a model of reinforcement learning.

[0091] Reinforcement learning is a framework in which an "agent," which is the subject of an "action," acquires a more suitable "action" through trial and error based on "experience." Here, "experience" corresponds to, for example, a "state" and / or a "reward" obtained by observation. For example, a Markov decision process is used as an example of a mathematical model that describes the interaction between an "agent" and an "environment." In the learning model shown in FIG. 6, a Markov decision process is used for one "agent" (single agent).

[0092] For example, in a Markov decision process, the probability of a state transition at a certain point in time is determined by the "state" prior to that point and the "action" at that point in time.

[0093] Reinforcement learning can be applied to the object to be controlled by modeling actions, states, rewards, etc., and defining criteria for determining appropriate actions (also called "policies").

[0094] In this embodiment, a reinforcement learning model applied to an LPWA network that operates in a frequency band in which a plurality of wireless systems coexist as described above will be described.

[0095] For example, in this embodiment, an "agent" corresponds to a "terminal" (e.g., an LPWA terminal). Therefore, in this embodiment, an environment in which multiple agents exist, that is, a multi-agent environment, may be used. In the following description, an "agent" and a "terminal" may be interchangeable.

[0096] Fig. 7 is a diagram showing an example of a multi-agent model In this embodiment, a multi-agent as shown in Fig. 7 is taken as an example.

[0097] Then, the "action" for each agent corresponds, for example, to a selection of a channel from among the candidate channels (channel allocation). For example, if the channel selection is performed by the base station, the "action" for each agent corresponds to a communication using the selected channel.

[0098] The "status" for each agent corresponds, for example, to the channel occupancy rate (usage rate) of each of the candidate channels and / or the reception level at the base station.

[0099] The "reward" for each agent corresponds to, for example, a reception result at the base station. For example, the reception result may be a reception success rate or an interval between multiple successful receptions (successful reception interval).

[0100] "Learning" corresponds to, for example, updating the criteria (strategies) for determining behavior in accordance with the above-mentioned "state" and / or "reward."

[0101] Here, in reinforcement learning, the more "actions" are taken and the more opportunities for "learning" that come with them, the more appropriate "standard (policy)" is reached.

[0102] In an LPWA network, compared to wireless LANs, the number of terminals is large, but the frequency of communication between each terminal is relatively low (in other words, the number of "actions" is relatively low). Therefore, when terminals learn individually, the opportunities for learning are reduced, learning does not progress, and it is difficult to reach a more appropriate "standard (measure)."

[0103] Therefore, in this embodiment, a learning device is provided in common between the terminals that are agents.

[0104] Fig. 8 is a diagram showing an example of a model in which a learning device is provided for each agent, and Fig. 9 is a diagram showing an example of a model in which a learning device shared between agents is provided.

[0105] Compared to Fig. 8, in Fig. 9, the actions of each agent and the state and / or reward for the actions are used in a learning device shared among agents. This makes it possible to speed up learning and easily reach a more appropriate "standard (policy)". In an LPWA network, the number of terminals is large, so the progress of learning can be improved.

[0106] In the above example, the "action" of each agent is channel selection, but the present disclosure is not limited to this. For example, the "action" of each agent may be other parameters set for communication (e.g., spreading factor, transmission power, modulation scheme and coding rate (MCS)), etc. Alternatively, the "action" of each agent may be a combination of two or more of channel selection and communication-related parameters.

[0107] Also, in the above example, the modeling may be common to each agent, or may be different. For example, the "action" of agent #1 may be the selection of a channel, and the "action" of agent #2 may be the setting of a spreading rate. In this case, as learning progresses, the selected channel becomes a more suitable channel for agent #1, and the set spreading rate becomes a more suitable spreading rate for agent #2.

[0108] <Processing Procedure> An example of a processing procedure between the terminal 30, the base station 10, and the centralized control server 20 in this embodiment will be described. Fig. 10 is a diagram showing an example of a processing procedure sequence in this embodiment. Fig. 10 shows an example in which the base station 10 includes the configuration of the centralized control server 20 described above.

[0109] The base station 10 performs radio wave monitoring (S100). For example, the base station 10 monitors the channel utilization rate of each candidate channel and measures the channel utilization rate. Radio wave monitoring may be performed continuously or periodically.

[0110] The channel utilization rate of a certain channel may be defined as the ratio of the time during which the channel is in use within a certain unit time to the unit time. For example, if a received power equal to or greater than a threshold is measured on a certain channel, the channel may be determined to be in use, and if a received power less than the threshold is measured on a certain channel, the channel may be determined to be not in use.

[0111] Alternatively, the channel utilization rate may be an average value over multiple unit times, rather than a local value. Alternatively, values ​​that are extremely different from the average may be removed from the channel utilization rates over multiple unit times, and the multiple channel utilization rates after removal may be averaged. The channel utilization rate may be subjected to such data processing (statistical processing) that improves the accuracy of the measurement value.

[0112] The terminal 30 performs a transmission process for a packet to be transmitted on an uplink (uplink packet) (S101). The base station 10 performs a reception process for the uplink packet (S102).

[0113] Then, the base station 10 determines the reception result of each candidate channel. For example, the base station 10 determines whether or not an uplink packet has been received from the terminal 30.

[0114] Then, the base station 10 records information on the reception result indicating whether the signal was received (reception OK) or not (reception NG) (S103). The recorded information on the reception result may include channel usage rate and reception power (e.g., RSSI). The recorded information may be at least one of the reception result, channel usage rate, and reception power. Alternatively, the recorded information may be other than these.

[0115] Here, when it cannot be determined that reception was not possible (reception NG), for example, the reception power may be low and it may not be possible to determine that a packet was transmitted from the terminal 30. For example, when an application that periodically receives packets from the terminal 30 is running, reception NG may be determined at regular intervals. In addition, when reception is NG, the reception power may be extremely low. When the reception power is extremely low and measurement is not possible, a specified value may be recorded instead of the measured value of the reception power. For example, the specified value in this case may be a value smaller than the minimum value of the measurable range of the reception power.

[0116] Next, the base station 10 performs a conversion process of the recorded information (S104). In this conversion process, for example, the recorded information is converted into data to be handled in the learning process of the learning device described above. For example, the reception power (e.g., RSSI) is converted into a value in the range from "0" to "1". Also, for example, if the reception result indicates reception OK, the reception result is converted into "+1", and if the reception result indicates reception NG, the reception result is converted into "-1". Also, the reception results for multiple packets may be converted into a reception success rate and / or a reception success time interval.

[0117] The base station 10 outputs the information that has been subjected to the conversion process to the learning device.

[0118] The learning device performs a learning process and determines a channel (an example of an action) to be assigned to the terminal 30 from among the candidate channels (S105). The learning algorithm used in the learning process is not particularly limited. The learning algorithm used in the learning process may be a general reinforcement learning algorithm. Examples of the reinforcement learning algorithm include Q-learning, SARSA, Actor-Critic, policy gradient method, DQN (Deep Q-Network), PPO (Proximal Policy Optimization), and REINFORCE, but in this embodiment, one of these reinforcement learning algorithms may be used, or an algorithm other than these may be used, or multiple reinforcement learning algorithms may be combined.

[0119] The base station 10 performs a transmission process of transmitting downlink control information including information of the determined channel to the terminal 30 (S106). For example, the base station 10 transmits a downlink control signal including the downlink control information to the terminal 30.

[0120] In an LPWA network, the reception timing of the terminal 30 may be limited. For example, in LoRa-WAN Class A, the time of downlink reception and the time of uplink transmission of the terminal 30 are set close to each other on the time axis in order to reduce the battery operating time of the terminal 30. For example, the timing of downlink reception of the terminal 30 is limited to a predetermined time after the uplink transmission of the terminal 30. The battery operating time of the terminal 30 is extended from the start timing of downlink reception to the end timing of uplink transmission.

[0121] In the reception process of S102, if the packet cannot be received (if reception is NG), the downstream control information does not need to be transmitted. However, if the timing of packet reception is known, for example, if an application that receives packets from the terminal 30 at a known timing is running, the downstream control information may be transmitted even if reception is NG.

[0122] The terminal 30 performs a receiving process of the downlink control information including the channel information (S107).

[0123] The terminal 30 performs a process (control reflection process) of reflecting the information included in the downlink control information in the control of the terminal 30 (S108). For example, the terminal 30 sets the channel indicated by the channel information as the channel for transmitting the uplink packet.

[0124] The terminal 30 uses the set channel to transmit an upstream packet, for example, at the time of the next upstream transmission.

[0125] 10, the base station 10 may perform reception processing on uplink packets (an example of a transmission signal) transmitted from the multiple terminals 30, and record information on the reception results of each of the multiple terminals 30. In this case, the base station 10 converts the information on the reception results of each of the multiple terminals 30, and outputs it to a common learning device.

[0126] 10 shows an example in which the base station 10 includes the configuration of the centralized control server 20 described above, but the base station 10 may have a configuration separate from the centralized control server 20. In this case, part of the processing shown in FIG. 10 may be executed by the base station 10, and the remaining part may be executed by the centralized control server 20.

[0127] For example, in S103, instead of recording the information on the reception result, the base station 10 may output the information on the reception result to the centralized control server 20. In this case, S104 and S105 may be executed by the centralized control server 20, and the centralized control server 20 may output information on the determined channel to the base station 10.

[0128] As described above, in this embodiment, the centralized control server 20 (an example of a control device) has a learning device common to the multiple terminals 30, and the learning device performs machine learning based on the reception results of signals transmitted from each of the multiple terminals 30, and determines channels (an example of parameters related to wireless communication) to be assigned to each of the multiple terminals 30. This makes it possible to easily control parameters related to wireless communication in response to changes in the wireless communication environment, without designing complex rules and adjusting parameters.

[0129] In the above example, an example of a learning model in which a common learning device is provided for each of the terminals 30 has been shown, but the present disclosure is not limited to this. Variations of the learning model will be described below.

[0130] <Variation 1> In the variation 1, an example in which a learning device is provided for each RAT (Radio Access Technology) will be described.

[0131] Fig. 11 is a diagram showing an example of a model including a learning device in Variation 1. As shown in Fig. 10, in Variation 1, a common learning device is provided between terminals (agents) of the same RAT. In this case, the learning results are common within the same RAT. Also, in this case, the learning devices of different RATs are different from each other.

[0132] For example, the LoRa system and the Wi-SUN system are different RATs. There may be a difference in communication performance between such different RATs. When a difference in communication performance occurs, the relationship (e.g., interference resistance characteristics, reception power characteristics, SINR characteristics) between the "state" (e.g., channel utilization rate and / or reception power) used for learning and the "reward" (e.g., reception result) differs for each RAT. For example, the LoRa system uses a spread spectrum system, and therefore has stronger resistance to interference than the Wi-SUN system. Therefore, for example, even if the reception power is the same between the LoRa system and the Wi-SUN system (i.e., even if the "state" is the same), the LoRa system will have a better reception result than the Wi-SUN system (i.e., a difference in the "reward" occurs).

[0133] In addition, the occupied bandwidth may differ between different RATs, and the number of candidate channels and / or the width of the channel may differ. For example, the width of a unit channel in the 920 MHz band is 200 kHz, and in the LoRa system, signals are transmitted with an occupied bandwidth of 125 kHz, while in the Wi-SUN system, signals are transmitted with an occupied bandwidth of 400 kHz. In this case, the LoRa system allocates in units of one channel, while the Wi-SUN system allocates in units of two channels. In this case, for example, the unit of one channel differs between the channel utilization rate corresponding to the "state" and the channel selection corresponding to the "action."

[0134] In consideration of the situation described above, by providing a learning device for each RAT, information corresponding to the "state," information corresponding to the "reward," and information corresponding to the "action" can be specified for each RAT, thereby obtaining more appropriate learning results for each RAT.

[0135] The learning devices for the above-mentioned RATs may be included in different centralized control servers 20, or may be included in a single centralized control server 20.

[0136] In addition, among the multiple RATs, a learning device may be common to some of the RATs. For example, among three RATs (RAT#1, RAT#2, and RAT#3), a common learning device #1 may be provided for RAT#1 and RAT#2, and a learning device #2 different from the learning device #1 may be provided for RAT#3.

[0137] Further, the present invention is not limited to the example in which a learning device is provided for each RAT, and a learning device may be provided for each setting.

[0138] For example, a learning device may be provided for each setting of the spreading factor (SF), which allows more suitable learning results to be obtained even when differences in communication performance arise due to differences in spreading gain.

[0139] Also, for example, a learning device may be provided for each bandwidth setting. Since the number of candidate channels changes depending on the bandwidth setting, a more suitable learning result can be obtained by providing a learning device for each bandwidth setting.

[0140] Further, the present invention is not limited to the example in which a learning device is provided for each RAT, and a learning device may be provided for each application.

[0141] For example, when settings differ for each application, differences in communication performance may occur between applications, or candidate channels may change for each application, so a learning device may be provided for each application. Also, when the quality required for each application differs, a performance index may change for each application, so a learning device may be provided for each application. Also, for example, a learning device may be provided for each application applied to a mobile terminal and a learning device may be provided for each application applied to a stationary terminal. Also, a learning device may be provided for each application with a different communication frequency.

[0142] <Variation 1 Processing Procedure> Next, the processing procedure of Variation 1 will be described with reference to the above-mentioned Fig. 10. For example, terminal #1 is a terminal of RAT #1, terminal #2 is a terminal of RAT #2, base station #0 corresponds to each of RAT #1 and RAT #2, and base station #0 has learning device #1 of RAT #1 and learning device #2 of RAT #2.

[0143] As in the example shown in FIG. 10, the base station 10 performs conversion processing of information (see S104 in FIG. 10) and outputs the converted information to the learning device. Here, in the case of information on the reception result of a packet transmitted from terminal #1, the information is output to learning device #1, and in the case of information on the reception result of a packet transmitted from terminal #2, the information is output to learning device #2. Then, the learning device #1 performs learning processing based on the acquired information and determines a channel to be assigned to terminal #1 from among the candidate channels. The learning device #2 performs learning processing based on the acquired information and determines a channel to be assigned to terminal #2 from among the candidate channels. Note that the candidate channels of the learning device #1 and the candidate channels of the learning device #2 may be partially or entirely common.

[0144] In the above-described processing procedure, two RATs and two learning devices are used as an example, but the present disclosure is not limited thereto. For example, the number of RATs may be one, or may be three or more.

[0145] Furthermore, even if the RAT is the same, a learning device may be provided according to parameter settings. For example, a learning device may be provided for each spreading factor of the LoRa system.

[0146] In addition, even if the RAT is the same, a learning unit may be provided depending on the application. For example, even if the LoRa method is the same, different learning units may be provided for a monitoring application in which a child owns a terminal and a parent watches over the child through the location information of the terminal, and an environmental sensing application in which many terminals are installed in factories, farms, etc. and sense the environment such as temperature and humidity.

[0147] <Variation 2> In the second variation, an example in which a learning device is provided for each base station 10 will be described.

[0148] Fig. 12 is a diagram showing an example of a model including a learning device in Variation 2. As shown in Fig. 11, in Variation 2, one learning device is provided in correspondence with one base station 10. In other words, a common learning device is provided between terminals connecting to the same base station 10. In this case, the learning results are common within the same base station. Also, in this case, the learning devices of different base stations are different from each other.

[0149] For example, the communication environment (e.g., reception state) of each of a plurality of base stations may differ depending on the installation location, etc. For example, a base station installed in a place with relatively few obstacles to radio wave propagation and a base station installed in a place with relatively many obstacles have different reception states, and therefore the obtained "state" (e.g., reception level) may differ.

[0150] In consideration of the situation described above, by providing a learning device for each base station, information corresponding to the "state," information corresponding to the "reward," and information corresponding to the "action" can be specified for each base station, thereby obtaining more appropriate learning results for each base station.

[0151] A learning device may be provided for each base station, and information may be exchanged between the learning devices. Fig. 13 is a diagram showing an example of a model in which information exchange is performed in Variation 2. Fig. 13 is the same as Fig. 12, except that learning device #1 and learning device #2 exchange information.

[0152] As shown in Fig. 13, each learning device independently performs learning processing, and the learning devices exchange information with each other and share some information. In other words, in the machine learning processing of learning device #1, information on the result (or progress) of the machine learning processing of learning device #2 is used. This may result in more suitable learning results. Note that the information to be shared here is not particularly limited.

[0153] <Variation 1 Processing Procedure> Next, the processing procedure of variation 2 will be described with reference to Fig. 10 described above. For example, base station #1 has a learning device #1, base station #2 has a learning device #2, terminal #1 connects to base station #1, and terminal #2 connects to base station #2. In this example, base station #1, base station #2, terminal #1, and terminal #2 may be of the same RAT.

[0154] As in the example shown in FIG. 10, the base station 10 performs conversion processing of information (see S104 in FIG. 10) and outputs the converted information to the learning device. Here, the base station #1 outputs information on the reception result of the packet transmitted from the terminal #1 to the learning device #1. The base station #2 outputs information on the reception result of the packet transmitted from the terminal #2 to the learning device #2. Then, the learning device #1 performs a learning process based on the acquired information and determines a channel to be assigned to the terminal #1 from among the candidate channels. The learning device #2 performs a learning process based on the acquired information and determines a channel to be assigned to the terminal #2 from among the candidate channels. Note that the candidate channels of the learning device #1 and the candidate channels of the learning device #2 may be partially or entirely common.

[0155] Here, the learning device #1 and the learning device #2 may exchange information. For example, when Q-learning is applied to the learning algorithm, the information to be exchanged may be a Q-value in Q-learning (for example, an action value function).

[0156] In the above-mentioned processing procedure, two base stations and two learning devices are used as an example, but the present disclosure is not limited thereto. For example, the number of base stations may be one, or may be three or more.

[0157] For example, among base stations #1 to #3, base stations #1 and #3 may have a common learning device #1, and base station #2 may have a learning device #2. For example, when base station #1 and base station #3 are adjacent base stations, they may share a common learning device.

[0158] <Variation 3> In Variation 3, for example, an example will be described in which the terminal 30 fails to receive downlink control information in S107 of FIG. 10 described above. In this example, the terminal 30 may autonomously select a channel to be used for communication. For example, the terminal 30 may randomly select a channel from among the candidate channels. Alternatively, the terminal 30 may have a history of channels used for communication and select a channel based on the history. For example, the terminal 30 may select a channel that was used immediately before the channel currently being used, and set it as the channel to be used at the next time point. Alternatively, the terminal 30 may calculate an average selection rate (average usage rate) for each of the candidate channels, and select a channel based on the calculated average selection rate.

[0159] <Variation 4> In Variation 4, an example will be described in which the centralized control server 20 selects multiple channels to be used for communication by a certain terminal 30 in descending order of priority, and transmits downlink control information including channel information of the selected multiple channels to the terminal 30. In this example, since the downlink control information includes channel information of multiple channels, if the terminal 30 fails to receive the downlink control information at a certain reception timing, the terminal 30 may select a channel to be used for communication by using downlink control information that has been received before the reception timing.

[0160] For example, the downlink control information may include channel information for each of a plurality of channels. For example, the downlink control information may include channel information for K channels from a first candidate channel to a Kth candidate channel in order of priority. Alternatively, the downlink control information may include information indicating the priority of each of a plurality of channels (for example, a selection probability).

[0161] When the terminal 30 is able to receive the downlink control information, the terminal 30 may set a channel to be used for communication (for example, uplink transmission) based on the received downlink control information.

[0162] Furthermore, when the terminal 30 is unable to receive the downlink control information, the terminal 30 may set a channel to be used for communication based on the downlink control information that was received before the point in time when the terminal 30 was unable to receive the downlink control information.

[0163] For example, the terminal 30 may set a channel to be used for the next communication to a channel with a lower priority than the channel used for communication before the point in time when the terminal 30 was unable to receive the downlink control information. Alternatively, the terminal may perform reselection based on the selection probability.

[0164] In addition, the expression "··· part" in the above embodiments may be replaced with other expressions such as "··· circuit", "··· device", "··· unit", or "··· module".

[0165] In addition, the term "channel" in the above embodiments may be replaced with other terms such as "frequency," "frequency channel," "band," "carrier," "subcarrier," or "(frequency) resource."

[0166] Furthermore, the term "calculate" in the above embodiments may be replaced with other terms such as "determine," "estimate," and "derive."

[0167] Furthermore, the term "classification" in the above embodiments may be replaced with other terms such as "separation" and "extraction."

[0168] The present disclosure can be realized in software, hardware, or software in conjunction with hardware.

[0169] Each functional block used in the description of the above embodiments may be partially or entirely realized as an LSI, which is an integrated circuit, and each process described in the above embodiments may be partially or entirely controlled by one LSI or a combination of LSIs. The LSI may be composed of individual chips, or may be composed of one chip that includes some or all of the functional blocks. The LSI may have data input and output. Depending on the degree of integration, the LSI may be called an IC, a system LSI, a super LSI, or an ultra LSI.

[0170] The method of integration is not limited to LSI, and may be realized by a dedicated circuit, a general-purpose processor, or a dedicated processor. Also, after LSI manufacturing, a programmable FPGA (Field Programmable Gate Array) or a reconfigurable processor that can reconfigure the connections and settings of circuit cells inside the LSI may be used. The present disclosure may be realized as digital processing or analog processing.

[0171] Furthermore, if a new integrated circuit technology that can replace LSI appears due to the progress of semiconductor technology or a derivative technology, it is possible to integrate the functional blocks using that technology. The application of biotechnology is also a possibility.

[0172] The present disclosure may be implemented in any type of apparatus, device, or system with communications capabilities (collectively, communications apparatus), including, but not limited to, telephones (e.g., cell phones, smartphones, etc.), tablets, personal computers (PCs) (e.g., laptops, desktops, notebooks, etc.), cameras (e.g., digital still / video cameras), digital players (e.g., digital audio / video players), wearable devices (e.g., wearable cameras, smart watches, tracking devices, etc.), game consoles, digital book readers, telehealth / telemedicine devices, communications-enabled vehicles or mobile conveyances (e.g., cars, planes, ships, etc.), and combinations of the above-mentioned devices.

[0173] Communications Equipment includes, but is not limited to portable or mobile equipment, non-portable or fixed equipment, devices and systems of any kind, such as smart home devices (appliances, lighting equipment, smart meters or metering devices, control panels, etc.), vending machines and any other "Things" that may exist on an Internet of Things (IoT) network.

[0174] Communications include data communications via cellular systems, wireless LAN systems, communications satellite systems, etc., as well as data communications via combinations of these.

[0175] A communications apparatus also includes devices, such as controllers and sensors, connected or coupled to a communications device that performs the communications functions described in this disclosure, such as controllers and sensors that generate control and data signals used by the communications device to perform the communications functions of the communications apparatus.

[0176] The communication apparatus also includes infrastructure facilities, such as base stations, access points, and any other apparatus, device, or system that communicates with or controls the various apparatuses listed above, but are not limited to these.

[0177] Although various embodiments have been described above with reference to the drawings, it goes without saying that the present disclosure is not limited to such examples. It is clear that a person skilled in the art can come up with various modified or amended examples within the scope of the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure. In addition, the components in the above-mentioned embodiments may be arbitrarily combined within the scope of the disclosure.

[0178] Although specific examples of the present disclosure have been described in detail above, these are merely examples and do not limit the scope of the claims. The technology described in the claims includes various modifications and alterations of the specific examples exemplified above. [Industrial Applicability]

[0179] The present disclosure is suitable for a wireless communication system. [Explanation of symbols]

[0180] 10 base station 101, 201, 301 Receiver 102 Demodulation / Decoding Unit 103 Interference Classification Unit 104, 202, 302 Control unit 105 Control signal generator 106 Encoding / Modulation Section 107, 203, 303 Transmitter 20 Centralized control server 30 Terminals

Claims

1. an acquisition unit that acquires, for each of a plurality of terminals including a first terminal and a second terminal, the first terminal and the second terminal being different from each other in at least one of a wireless communication method, a base station to be wirelessly connected, setting information related to wireless communication, and an application being operated, a reception result indicating a result of a reception process for a signal transmitted from each of the terminals; A control unit that centrally controls the plurality of terminals, Based on a first reception result indicating a result of the reception processing for the signal transmitted from the first terminal, a first machine learning common to the first terminal is performed, and parameters related to wireless communication used by the first terminal are determined; a control unit that performs second machine learning common to the second terminal based on a second reception result indicating a result of the reception processing for the signal transmitted from the second terminal, and determines parameters related to wireless communication used by the second terminal; A control device comprising:

2. The parameters include at least one of a channel used by the terminal, a transmission power, and a spreading factor. The control device according to claim 1 .

3. The first reception result indicates at least one of whether the reception of the signal transmitted from the first terminal was successful, a reception success rate of the signal transmitted from the first terminal, and a reception success time interval of the signal transmitted from the first terminal; The second reception result indicates at least one of whether the reception of the signal transmitted from the second terminal was successful, a reception success rate of the signal transmitted from the second terminal, and a time interval of successful reception of the signal transmitted from the second terminal. The control device according to claim 1 .

4. The control unit uses information obtained in the second machine learning in the first machine learning. The control device according to claim 1 .

5. When the first reception result indicates that reception of the signal transmitted from the first terminal has not been successful, the control unit does not determine the parameters to be used by the first terminal that transmitted the signal. The control device according to claim 1 .

6. The control unit determines the plurality of parameters in order of priority. The control device according to claim 1 .

7. The terminal and the control device are applied to a Low Power Wide Area (LPWA) network. The control device according to claim 1 .

8. A control device comprising: Acquire, for each terminal, a reception result indicating a result of a reception process on a signal transmitted from each of a plurality of terminals including a first terminal and a second terminal, the first terminal and the second terminal being different from each other in at least one of a wireless communication method, a base station to be wirelessly connected, setting information related to wireless communication, and an application being operated; Based on a first reception result indicating a result of the reception processing for the signal transmitted from the first terminal, a first machine learning common to the first terminal is performed, and parameters related to wireless communication used by the first terminal are determined; performing a second machine learning common to the second terminal based on a second reception result indicating a result of the reception processing for the signal transmitted from the second terminal, and determining parameters related to wireless communication used by the second terminal; Control methods.

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