Control device for setting and operating o-ran, processing device, control method, processing method and program

Abstract

To provide a technique for improving accuracy of control of a RAN in a communication system using an O-RAN.SOLUTION: A control device functioned as a Non-Real Time RAN Intelligent Controller (non-real time RIC) in an Open-Radio Access Network (O-RAN) receives from an E2 node first information that the E2 node has, the first information being available for the non-real time RIC to control a RAN, transmits a request message requesting provision of second information different from the first information to a quasi-real time RIC, the second information including information collected from the E2 node by the quasi-real time RIC or information generated by the quasi-real time RIC and being available for the non-real time RIC to control the RAN, receives the second information transmitted from the quasi-real time RIC, and controls the RAN using the first information and the second information.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a technique for setting up and operating an O-RAN (Open-Radio Access Network). [Background technology]

[0002] Standardization of O-RAN (Open-RAN), which makes radio access networks (RAN) more open and intelligent, is underway. In O-RAN, a RAN Intelligent Controller (RIC) is defined to intelligently configure and operate the RAN by utilizing machine learning and other techniques using information measured within the RAN. Two types of RIC are defined: non-real-time RIC and quasi-real-time RIC, which have different control periods. Non-patent document 1 describes a method (interface, etc.) for exchanging messages between non-real-time RIC and quasi-real-time RIC. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] O-RAN Working Group 2, “A1 Interface:Application Protocol v04.00”, O-RAN Alliance, 2023 Summary of the Invention [Problem to be solved by the invention]

[0004] The present invention provides a technique for improving the accuracy of RAN control in a communication system using O-RAN. [Means for solving the problem]

[0005] A control device according to one embodiment of the present invention is a control device that functions as a Non-RealTime RAN Intelligent Controller (non-real-time RIC) in an Open-Radio Access Network (O-RAN), and includes a first receiving means for receiving from an E2 node first information that can be used by the non-real-time RIC to control the RAN, the first information being possessed by the E2 node, a transmitting means for transmitting a request message requesting the quasi-real-time RIC to provide the second information that is different from the first information and includes information collected by the quasi-real-time RIC from the E2 node or information generated by the quasi-real-time RIC and can be used by the non-real-time RIC to control the RAN, a second receiving means for receiving the second information transmitted from the quasi-real-time RIC, and a control means for controlling the RAN using the first information and the second information.

[0006] A processing device according to one embodiment of the present invention is a processing device that functions as a Near-RealTime RAN Intelligent Controller (quasi-real-time RIC) in an Open-Radio Access Network (O-RAN), and has a receiving means for receiving from the non-real-time RIC a request message requesting the provision of the second information that is different from first information that a non-real-time RIC can receive from an E2 node, the second information including information collected by the quasi-real-time RIC from the E2 node or information generated by the quasi-real-time RIC and that can be used by the non-real-time RIC to control the RAN, and a transmitting means for providing the second information to the non-real-time RIC. Effect of the Invention

[0007] According to the present invention, it is possible to improve the accuracy of RAN control in a communication system using O-RAN. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 illustrates an example of the configuration of a communication system. [Diagram 2] FIG. 11 is a diagram illustrating an example of a sequence between a control device and a processing device. [Diagram 3] FIG. 4 is a diagram illustrating an example of the operation of the control device. [Figure 4] FIG. 13 is a diagram illustrating an example of the operation of the processing device. [Diagram 5] FIG. 4 is a diagram illustrating an example of the operation of the control device. [Figure 6] FIG. 13 is a diagram illustrating an example of the operation of the processing device. [Figure 7] FIG. 2 is a diagram illustrating an example of a hardware configuration of a control device and a processing device. [Figure 8] FIG. 2 is a diagram illustrating an example of a functional configuration of a control device. [Figure 9] FIG. 2 illustrates an example of a functional configuration of a processing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the invention according to the claims, and not all combinations of features described in the embodiments are essential to the invention. Two or more features among the multiple features described in the embodiments may be arbitrarily combined. Also, the same reference numbers are used for the same or similar configurations, and duplicated descriptions are omitted.

[0010] (System Configuration) FIG. 1 shows an example of the configuration of a communication system according to this embodiment. This communication system is configured using an Open-Radio Access Network (O-RAN), which is being standardized to open up and make the Radio Access Network (RAN) intelligent. The O-RAN is configured to include, for example, an SMO 101, a control device 102 in the SMO 101, a processing device 103, and an E2 node 104. SMO is an abbreviation for Service Management and Orchestration. The SMO 101 monitors, manages, and controls the entire system. The control device 102 and the processing device 103 cooperate with each other to design and set parameters of the RAN, automate and optimize the operation of the RAN, and the like. The control device 102 may be a Non-RealTime RAN Intelligent Controller (non-real-time RIC) defined in the O-RAN standard. The processing device 103 may be a Near-RealTime RIC (quasi-real-time RIC) defined in the O-RAN standard. The control device 102 and the processing device 103 may be separate entities, or may be implemented in a single piece of hardware. The control device 102 performs the determination of a policy for controlling the long-term behavior of the entire system. For example, the control device 102 generates a trained model for predicting the communication quality (throughput, delay, etc.) of the RAN using machine learning, and generates a policy for controlling the RAN. The processing device 103 controls the short-term behavior of the E2 node 104. For example, the processing device 103 predicts the communication quality of the RAN using the trained model generated by the control device 102, and controls the RAN according to the policy generated by the control device 102. The E2 node 104 is, for example, an O-RAN Central Unit (O-CU), an O-RAN Distributed Unit (O-DU), etc. The O-CU has a function of establishing and disconnecting connections between the O-DU, O-RU, and User Equipment (UE) connected thereto, controlling communication, etc. The O-CU performs, for example, communication control such as control signaling, and transfer processing for communicating user plane data with a terminal device.In addition, O-RU is an abbreviation of O-RAN Radio Unit. In one example, when the O-CU performs processing of higher layers of communication processing with the UE, the O-DU can perform processing of lower layers of the communication processing below the medium access control (MAC) layer.

[0011] An interface between the SMO 101 and each of the processing device 103 and the E2 node 104 may be called an O1 interface. The SMO 101 may acquire performance information, fault information, signaling information, information on the characteristics of user data, and the like accumulated in the E2 node 104 from the E2 node 104 using the O1 interface. The control device 102 included in the SMO 101 may generate setting parameters optimized for the wireless environment and traffic load, for example, using the information acquired by the SMO 101. The processing device 102 may be separate from the SMO 101. The SMO 101 may provide the setting parameters generated by the control device 102 to the E2 node 104 using the O1 interface.

[0012] The interface between the control device 102 and the processing device 103 may be called an A1 interface. As an example, the control device 102 may generate a policy for controlling the RAN using information acquired by the SMO 101, and provide the policy to the processing device 103 using the A1 interface. In this embodiment, the policy generated by the control device 102 for controlling the RAN is called an A1 policy. The A1 policy may be called by other names. The A1 policy may also include performance targets for communication quality (throughput, delay time, etc.) for a specific user, slice, cell, etc. The control device 102 may also provide a learned model generated by the control device 102 to the processing device 103 using the A1 interface.

[0013] The interface between the processing device 103 and the E2 node 104 may be called an E2 interface. The processing device 103 may obtain information from the E2 node 104 using the E2 interface and perform analysis using the obtained information. The processing device 103 may also control the E2 node 104 using the results of its own analysis in accordance with the A1 policy provided by the control device 102. For example, the processing device 103 may execute a handover instruction or the like to the E2 node 104. In this way, information exchange and control are performed between the devices constituting the O-RAN using interfaces defined between them. Note that the information exchange and control between the devices may be performed using interfaces other than those described above, such as a Y1 interface or an O2 interface.

[0014] As described above, the control device 102 and the processing device 103 cooperate with each other to set up and operate the RAN. However, the information available to the control device 102 and the processing device 103 is different. For example, the processing device 103 can acquire measurement information for each UE, such as communication quality in a cell to be controlled, from the E2 node 104 by using the E2 interface. On the other hand, the measurement information that the control device 102 can acquire via the O1 interface is information for each cell. That is, the information available to the control device 102 may be coarser in granularity than the information available to the processing device 103. Here, it is considered that the control device 102 generates a trained model by machine learning using the acquired measurement information as input, the processing device 103 predicts the communication quality of the RAN by executing inference using the trained model, and the processing device 103 controls the E2 node 104. In this case, if the teacher data available as an input for machine learning by the control device 102 is measurement information for each cell (for example, the average value or total value of throughput and delay time), the communication quality that can be predicted in the future may also be information for each cell. Therefore, for example, in a situation where fine control per UE is required, a learned model with the required granularity cannot be generated, and highly accurate control of the RAN may not be possible. As an example, the A1 policy generated by the control device 102 may include a performance target per UE. In this case, if the measurement information in the RAN that the control device 102 can acquire is only information per cell, the control device 102 cannot grasp the achievement status of the performance target of each UE in the actual RAN. Therefore, there may be a case where the performance target for each UE set by the control device 102 is different from the actual communication quality status in the RAN. In this way, the information available to the control device 102 is limited, and this may result in a situation where the RAN is not configured or operated according to the required accuracy.

[0015] In this embodiment, in consideration of such a situation, an interface is provided between the control device 102 and the processing device 103 so that the control device 102 receives information held by the processing device 103. An example of the exchange of messages and measurement information between the control device 102 and the processing device 103 in this embodiment will be described below.

[0016] (Controller Request for Data) Fig. 2 shows an example of a sequence between the control device 102 and the processing device 103. This sequence can be executed using, for example, the A1 interface. Note that this sequence may be executed using an O1, Y1, A1-EI interface, etc. other than the A1 interface. Also, while Fig. 2 shows an example in which messages are directly exchanged between the control device 102 and the processing device 103, messages may be exchanged indirectly via, for example, other components in the O-RAN.

[0017] First, the control device 102 transmits a request message to the processing device 103 requesting the provision of measurement information held by the processing device 103 (S201). The request message may be called another name, for example, Data Collection Request. When the processing device 103 receives the request message, it determines whether or not the measurement information can be provided, and transmits the determination result to the control device 102 as a response message (S202). The response message may be called another name, for example, Data Collection Response. When the processing device 103 accepts the provision of the measurement information, it starts providing the measurement information according to the request included in the request message after transmitting the response message (S203). Note that, when the processing device 103 accepts the request, it may start providing the measurement information without transmitting a response message. Also, the response message and the measurement information may be transmitted simultaneously or in the same message. When the processing device 103 does not accept the request included in the request message, it may transmit a response message including a reason for refusal. The processing device 103 may notify the control device 102 of, for example, the reason for rejection, that the processing device 103 does not have the requested measurement information, that the processing device 103 does not have a function for performing processing required to provide the requested measurement information, etc. If the processing device 103 does not have the requested measurement information at the time of receiving a request message from the control device 102, the processing device 103 may perform new measurement or collect information to provide the information to the control device 102. The processing device 103 may also transmit a message for starting a sequence related to the provision of the measurement information before the control device 102. For example, the processing device 103 may periodically poll the control device 102. The request message or the response message may be transmitted integrated with another message.

[0018] (Specifying measurement information in the request message) The request message may include, for example, information specifying a period during which the measurement information is measured (which may be called a measurement period, or measurement time). The measurement period may include information specifying one or more of a time when the measurement starts (which may be called a measurement start time), a time when the measurement ends (which may be called a measurement end time), and an interval during which the measurement is performed (which may be called a measurement period). The request message may also include, for example, information specifying a period during which the measurement information is provided (which may be called a reporting period, or reporting time). The providing period may include information specifying one or more of a time when the provision starts (which may be called a reporting start time), a time when the measurement ends (which may be called a reporting end time), and an interval during which the provision is performed (which may be called a reporting period). The control device 102 may specify an appropriate cycle or period of the measurement period or the providing period according to the purpose of using the measurement information, the characteristics of the measurement information, and the like, and notify the processing device 103 using the request message.

[0019] The request message may include information specifying a procedure (which may be called a collection method) for providing the measurement information. For example, as an example of the providing procedure, the processing device 103 may periodically transmit the measurement information over a specified providing period. Such a providing procedure may be called streaming. For example, when the control device 102 changes or adds an A1 policy to reflect the status of the RAN, it may be appropriate for the measurement information to be provided in real time. In such a case, the control device 102 may request the periodic provision of the measurement information in the request message so that the measurement information can be used timely for generating, changing, adding, or the like the A1 policy. Also, as an example of the providing procedure, the processing device 103 may collect information collected over a specified measurement period into one or more files and provide the collected information to the control device 102 in a lump. Such a providing procedure may be called file-based. For example, the measurement information used for machine learning may have a large data size, so that the A1 interface may be occupied for a long time when the measurement information is provided. Also, processing such as preprocessing may be required for the measurement information used for machine learning. In such a case, the control device 102 may request that the measurement information be provided after performing processing such as compression of the measurement information or preprocessing for machine learning after the end of the measurement period, or during a time when the usage rate of the A1 interface is low. As described later, a method for processing the measurement information (which may be called a Processing method) may be specified in the request message. Note that the measurement information may be provided by a method other than the above-mentioned providing procedure. The processing device 103 provides the measurement information to the control device 102 according to the specified procedure.

[0020] The request message may include information for identifying the type of measurement information (which may be called data name), for example. As an example, the measurement information may include measurement information of each category, namely, measurement information specified in other O-RAN interfaces other than the A1 interface (which may be called O-RAN interface data), measurement information newly specified in the A1 interface (which may be called interface specific data), and measurement information specified by a product development vendor (which may be called vendor specific data). For example, the measurement information specified in other O-RAN interfaces other than the A1 interface is measurement information exchanged using an interface between the processing device 103 and other devices, for example, measurement information specified in interfaces such as E2, A1-EI, and Y1. When the measurement information requested by the request message is the same as the measurement information specified in other interfaces, the parameter names associated with these measurement information are used instead of newly specifying the measurement information in the A1 interface, thereby avoiding the complication of the same measurement information being given different names. The parameter names of such measurement information specified in the existing O-RAN interface may be written as "OR.DataName". "OR" is a prefix indicating that this measurement information is measurement information defined in another O-RAN interface, and "DataName" is a parameter name defined in the other interface. Furthermore, measurement information newly defined in the A1 interface is measurement information not defined in another O-RAN interface, and a new parameter name, etc. may be defined in the A1 interface. For example, information newly generated by the processing device 103 by analyzing the measurement information or newly generated by processing the measurement information, etc. may be linked to a new parameter name and provided to the control device 102. Such a parameter name of measurement information newly defined in the A1 interface may be written as "IS.DataName". "IS" is a prefix indicating that it is newly defined, and "DataName" is a parameter name linked to the measurement information.Furthermore, measurement information that is not specified as an O-RAN interface and is specified independently by a product development vendor may be linked to a free parameter name that the product vendor specifies. For example, in the processing device 103, information generated by a process unique to the product vendor may be linked to a parameter name uniquely generated by the product vendor and provided to the control device 102. Such a parameter name of measurement information uniquely specified by the product vendor may be written as "VS.DataName". "VS" is a prefix indicating that it is uniquely specified by the product vendor, and "DataName" is a parameter name linked to the measurement information. Note that the type of measurement information may include other types than those mentioned above. Also, one request message may include one or more pieces of information that specify the type of measurement information. The information that specifies the type of measurement information may be information that specifies any one of a parameter name, a category, and a prefix, or may be a combination of these.

[0021] The request message may include, for example, information (which may be called a Scope identifier) ​​that identifies a unit (or a range) of the measurement information. The information that identifies the unit of the measurement information may include an identifier (cell ID) that uniquely identifies a certain cell, an identifier (UE ID) that uniquely identifies a certain UE, a condition (UE group) for identifying a plurality of UEs that satisfy a predetermined condition, an identifier (slice ID) that uniquely identifies a certain slice, and an identifier (QoS ID) that uniquely identifies a certain QoS flow. For example, the slice ID may be S-NSSAI (Single-Network Slice Selection Assistance Information). The QoS ID may be Quality flow Indicator (QFI) or 5G QoS Indicator (5QI). The information that identifies the unit of the measurement information may be other than the above. A single request message may include a plurality of pieces of information that identify the unit of the measurement information. For example, the control device 102 may request the same type of measurement information for the same period in a plurality of different units in order to generate a trained model corresponding to each unit of the measurement information or a trained model that combines them according to the purpose of use. In addition, two or more pieces of information that identify the unit of the measurement information may be combined. For example, when a combination of a UEID and a slice ID is used, only the measurement information of the slice corresponding to the specified S-NSSAI in the UE corresponding to the specified UEID is provided. In this case, it is possible to generate a more accurate learned model based on the traffic characteristics of the specified slice and to set an A1 policy with finer granularity. Also, for example, when a combination of a UEID and a QoSID is used, it is possible to use measurement information with finer granularity than a slice. On the other hand, when a combination of a cell ID and a slice ID or a QoSID is used, the control device 102 can use an average or a total for each slice or QoS flow in multiple UEs. By using more measurement information, it is possible to generate a learned model or an A1 policy that is less dependent on the location of the UE, for example.Furthermore, when generating an A1 policy or a learned model for a UE that satisfies a specific condition, the control device 102 may request measurement information of a UE group that groups UEs that satisfy this condition. Note that the UE group may be combined with a slice ID or a QoS ID.

[0022] In this way, the control device 102 can use the measurement information held by the processing device 103 for control to improve the accuracy of RAN control by receiving the information in a procedure or unit according to the purpose. In addition, by specifying the type, unit, procedure, etc. of the requested measurement information, it is possible to reduce the amount of traffic transferred using the A1 interface and to level out the utilization rate of the A1 interface.

[0023] (RAN control operation using measurement information) The control device 102 executes processing for setting and operating the RAN using the measurement information provided from the processing device 103. FIG. 3 shows an example of the operation of the control device 102 in RAN control using the measurement information. In the present embodiment, as an example, the control device 102 generates a learned model for predicting the future throughput of each UE using measurement information related to the communication quality of each UE. Examples of the measurement information related to the communication quality may be received signal strength indicator (RSSI), signal-to-interference-plus-noise ratio (SINR), throughput, delay time, and the like. For example, it is assumed that the control device 102 sets the throughput of each UE in a certain slice to be 10 Mbps or more as an A1 policy and provides this A1 policy to the processing device 103 (S301). At this time, the control device 102 requests the processing device 103 to provide time-series measurement information related to the communication quality of each UE in this slice (S302). For example, the control device 102 specifies an S-NSSAI corresponding to this slice as a slice ID in a request message, and specifies an ID corresponding to a UE using this slice as a UE ID. In addition, the control device 102 may specify measurement information related to communication quality such as throughput, RSSI, and SINR in the request message as the type of measurement information. In addition, the control device 102 may specify a procedure for providing the measurement information to be provided in a lump after the measurement is completed, and may specify a method for processing the measurement information, in order to use the measurement information as an input for machine learning. Then, the control device 102 executes machine learning using the time-series measurement information provided from the processing device 103 as an input, and generates a trained model (S303). For example, the control device 102 acquires from the processing device 103 time-series measurement information (first measurement information) of the communication quality of each UE for the past 20 seconds from a certain reference time, and time-series measurement information (second measurement information) of the throughput of each UE for the past 10 seconds after the reference time. The control device 102 performs machine learning using teacher data with the first measurement information as input data and the second measurement information as correct answer data, and generates a trained model. The training data used by the control device 102 and the trained model generated are not limited to the measurement information related to the communication quality, and may be combined with other available information to perform machine learning.The generated trained model is provided to the processing device 103 via the A1 interface (S304).

[0024] The processing device 103 executes control of the E2 node using the trained model provided from the control device 102. FIG. 4 shows an example of the operation of the processing device 103 in this embodiment. First, the processing device 103 receives the trained model from the control device 102 (S401). For example, the trained model may be provided as a program executable by a computer included in the processing device 103. The processing device 103 collects measurement information to be input to the trained model (S402). The measurement information to be input to the trained model may be acquired, for example, from the E2 node via the E2 interface. In addition, the measurement information stored in a storage medium included in the processing device 103 may be used. Then, the processing device 103 executes future prediction of the communication quality of the RAN by inference using the trained model (S403). In this embodiment, as an example, the processing device 103 performs inference of the throughput of each UE for 10 seconds from the current time using time-series measurement information for the past 20 seconds from the current time for the same type and unit of measurement information as the measurement information used by the control device 102 as the teacher data. The processing device 103 controls the E2 node 104 based on the result of the inference analysis (S404). In this embodiment, when there is a UE whose inference result is below the setting in the A1 policy, the processing device 103 instructs the E2 node 104 to hand over the UE to another adjacent cell, for example. In this way, the control device 102 generates a trained model using the communication quality for each UE, and the processing device 103 can predict the communication quality for each UE using this trained model and perform RAN control with fine granularity based on this prediction. Note that the control device 102 may update the trained model by receiving periodic provision of measurement information. By updating the trained model, the processing device 103 can maintain an appropriate prediction of communication quality according to changes in the communication quality of the RAN. Furthermore, when the control device 102 can use measurement information from a plurality of processing devices 103, the control device 102 can perform machine learning using more measurement information. By using measurement information received from a wide range of areas, a general-purpose trained model that is less susceptible to the influence of a specific area can be generated.Even when only the measurement information of one processing device is used, the control device 102 is generally implemented by a computer with higher performance than the processing device 103, and therefore, by having the control device 102 analyze the measurement information, there is an advantage that a large amount of measurement information can be processed at high speed. On the other hand, when the control device 102 receives the measurement information of each UE for each slice or QoS flow, multiple trained models may be generated for each unit. By using the trained model generated for each slice or QoS flow, it is possible to execute control based on highly accurate predictions based on differences in communication traffic characteristics, etc.

[0025] FIG. 5 shows another example of the operation of the control device 102 in RAN control using measurement information. In this embodiment, the control device 102 may change or add the A1 policy by receiving measurement information on communication quality for each UE from the processing device 103. For example, in a certain cell, it is assumed that 30% of the resource blocks in the entire cell are allocated to a certain slice. The resource block is a unit of available radio resources to be allocated to each UE, each slice, etc. in a cell, etc. For example, it is assumed that the control device 102 sets the throughput of the RAN of each UE to 10 Mbps or more as the performance target of this slice as the A1 policy, and provides this A1 policy to the processing device 103 (S501). At this time, the control device 102 requests the processing device 103 to provide, for example, measurement information on the number of resource blocks used and the throughput of each UE in this slice (S502). For example, in the request message, the control device 102 specifies the S-NSSAI corresponding to this slice as the slice ID, and specifies the ID corresponding to the UE using this slice as the UE ID. In addition, in the request message, the control device 102 may specify, as the type of measurement information, the number of resource blocks in use, throughput, and measurement information related to communication quality such as RSSI and SINR. Note that the control device 102 specifies periodic provision as a procedure for providing the measurement information in order to use the measurement information for verifying the A1 policy. The control device 102 then verifies the A1 policy using the measurement information provided from the processing device 103, and generates the A1 policy as necessary (S503). For example, the control device 102 may calculate the usage rate of the resource blocks of this slice in this cell from the total number of resource blocks in use for each UE that has been provided. In addition, the control device 102 may predict the throughput of each UE from the measurement information of the throughput for each UE, for example, by analysis using a predetermined algorithm or inference using a learned model.Here, if the total resource block usage rate of this slice exceeds a predetermined threshold (e.g., 27% of the resource blocks in the entire cell are used) and the predicted throughput of a specific UE does not satisfy the A1 policy (e.g., less than 10 Mbps), the control device 102 generates a new A1 policy for load balancing and provides it to the processing device 103 (S504). For example, the new A1 policy specifies this cell and this slice, and sets the resource block usage rate to 24% or less.

[0026] FIG. 6 shows another example of the operation of the processing device 103 in this embodiment. The processing device 103 receives the A1 policy from the control device 102 in S504 (S601). The processing device 103 uses the received A1 policy to control the E2 node 104. For example, the processing device 103 collects measurement information required to execute the A1 policy from the E2 node 104 (S602). For example, the processing device 103 collects measurement information for identifying the usage rate of resource blocks in a cell and slice set in the A1 policy. The measurement information for identifying the usage rate of resource blocks may be the number of resource blocks used in the cell. The processing device 104 also collects information for identifying the throughput of each UE. The processing device 103 performs analysis using the collected measurement information and determines whether the A1 policy is satisfied (S603). This analysis may be performed, for example, by inference using a learned model with the collected measurement information as input or by determination using a predetermined algorithm. The processing device 103 controls the E2 node based on the result of the analysis (S604). For example, the processing device 103 determines that some UEs are to be handed over because the analysis result shows that the resource blocks used by the cells and slices set in the A1 policy are 27% of the entire cells, which exceeds the threshold value set in the A1 policy (24% of the entire cells). In addition, the processing device 103 selects UEs whose throughput prediction is determined not to satisfy the A1 policy (less than 10 Mbps) as targets for handover based on these determination results. Based on these determination results, the processing device 103 instructs the E2 node 104 to hand over the selected UEs to an adjacent cell (S604). In this way, the control device 102 receives fine-grained measurement information from the processing device 103, verifies the A1 policy using this measurement information, and provides the generated A1 policy to the processing device 103. This makes it possible to perform RAN configuration and operation with high accuracy.

[0027] (Operation when processing measurement information) When the control device 102 generates a trained model using the measurement information received from the processing device 103 and the processing device 103 performs inference using this trained model, the formats of the measurement information used by the control device 102 and the processing device 103 must match. In particular, when the control device 102 performs preprocessing such as normalizing the measurement information or interpolating missing data when generating a trained model, the processing device 103 must also perform inference using measurement information that has been similarly preprocessed, otherwise a correct inference result cannot be obtained. In this embodiment, the control device 102 provides a function of notifying the processing device 103 of a method for processing the measurement information. Note that the processing device 103 may specify a method for processing the measurement information for the control device 102. For example, when the measurement information specified in the request message is to be processed, the control device 102 may notify the processing method within the request message. In addition, the method by which the control device 102 notifies the processing method of the measurement information is not limited to the request message, and a sequence for notifying the processing method may be newly provided in the A1 interface. By providing an independent sequence for the request message, the control device 102 may specify a wide range of measurement information as the object of processing. For example, the control device 102 may request the processing device 103 to always execute a specified processing process for a specific type of measurement information. In addition, when a trained model is provided from the control device 102 to the processing device 103, a method for preprocessing the measurement information to be input to the trained model may be provided. In this case, the control device 102 may select a different processing method to preprocess the measurement information each time a trained model is generated, and notify the processing device 103 of the selected processing method each time. The processing device 103 may process the measurement information according to the processing method specified by the request message or a sequence for notifying the processing method, and provide it to the control device 102. Note that when the processing device 103 provides the measurement information to the control device 102, the processing device 102 may process the measurement information provided. In this case, when the processing device 103 executes inference using the trained model provided by the control device 102, the processing device 103 processes the input data of the trained model using the processing method specified by the control device 102.In addition, the processing of the measurement information is not limited to preprocessing for generating a trained model, but may be other processing such as compression to reduce the data size of the measurement information or encryption to exchange information securely.

[0028] (Specifying the processing method) The control device 102 may specify the processing method by using a mathematical expression, for example. The mathematical expression may include, for example, an expression by a pair of a condition and an operation. For example, when the measurement information to be processed is the throughput for each UE, the processing method is (Condition 1) if the throughput value exceeds 10 Mbps, (Operation 1) replace it with 10 Mbps, and (Condition 2) normalize the entire measurement information between 0 and 1 (Operation 2). In this case, each pair of Condition 1 and Operation 1 and Condition 2 and Operation 2 may be notified to the processing device 103 in the request message. The processing device 103 determines whether each of the requested measurement information satisfies each specified condition, and if the condition is satisfied, performs an operation corresponding to the condition and provides the measurement information to the control device 102. The processing method may be duplicate deletion or missing value complementation for generating teacher data to be used in machine learning. In the case of duplicate deletion, for example, the condition is that an identification number identifying each measurement information is duplicated with other measurement information, and the operation is to delete the measurement information. In addition, in the case of missing value complementation, for example, the condition is that there is a missing piece of measurement information, and the operation is to delete this data or to replace it with an average value or a representative value of all the measurement values. Note that the mathematical expression is not limited to the condition and operation, and may include any item or expression that specifies the condition or operation to be processed.

[0029] The control device 102 may specify a processing method by specifying a function corresponding to the processing method. For example, the control device 102 may share with the processing device 103 in advance the functions used in processing the measurement information and the identifiers that identify each function. In this case, the control device 102 may specify the processing method by notifying the processing device 103 of the identifiers corresponding to the functions used in the processing. By sharing the functions between the control device 102 and the processing device 103 in advance, it is possible to reduce information that specifies each time a complex processing is performed. As an example, the control device 102 requests the processing device 103 to register any function that includes a formula or the like together with an identifier. By checking the response of the processing device 103 to this request, information on the functions that can be specified between the devices may be shared. Note that, if an argument is required to execute processing using a function, the control device 102 may notify the argument together with the function specification.

[0030] The control device 102 may specify the processing method by specifying an xApp corresponding to the processing method in the request message. The xApp is, for example, an application that performs analysis and control of various information on the framework of the processing device 103. For example, the control device 102 may share with the processing device 103 in advance the contents of the processing performed by the xApp and an identifier that identifies each xApp. The control device 102 may specify the processing method by notifying the processing device 103 of an identifier corresponding to the xApp used for the processing. As an example, the control device 102 may request the processing device 103 to install the xApp. By checking a response to this request indicating the completion of installation of the processing device 103, information on the xApp that can be specified between the devices may be shared in advance. Note that, when an input parameter is required for the execution of the xApp, the control device 102 may notify the input parameter together with the identification of the xApp. Even when a complex processing is performed on the measurement information, the processing method can be easily notified by identifying the xApp.

[0031] (Hardware configuration) Next, a configuration example of the control device 102 and the processing device 103 as described above will be described. FIG. 7 is a diagram showing the hardware configuration of the control device 102 and the processing device 103. In one example, the control device 102 and the processing device 103 are configured to include a processor 701, a ROM 702, a RAM 703, a storage device 704, and a communication circuit 705. The processor 701 is a computer configured to include one or more processing circuits such as a general-purpose CPU (Central Processing Unit) or an ASIC (Application Specific Integrated Circuit). The processor 701 reads and executes programs stored in the ROM 702 and the storage device 704 to execute the overall processing of the device and each of the above-mentioned processes. The ROM 702 is a read-only memory in which information such as programs and various parameters related to the processing executed by the control device 102 and the processing device 103 is recorded. The RAM 703 functions as a workspace when the processor 701 executes a program, and is a random access memory in which temporary information is recorded. The storage device 704 is, for example, configured by a removable external storage device or the like. The communication circuit 705 includes, for example, a circuit for communicating with other devices. As an example, the communication circuit 705 may function as an A1 interface, an O1 interface, an E2 interface, etc. Although one communication circuit 705 is illustrated in FIG. 7, each device may have multiple communication circuits.

[0032] (Functional configuration) FIG. 8 is a diagram showing an example of the functional configuration of the control device 102. The control device 102 includes, as its functions, a first acquisition unit 801, a request unit 802, a second acquisition unit 803, a processing specification unit 804, a processing information sharing unit 805, a processing unit 806, a model generation unit 807, a model provision unit 808, and a RAN control unit 809. FIG. 8 shows the functional configuration of the control device 102 of this embodiment, and, for example, a general configuration of the control device is omitted. Note that these functional units can be realized, for example, by the processor 701 executing a program stored in the ROM 702 or the storage device 704 and controlling the communication circuit 705 as necessary. However, this is not limited to this, and for example, dedicated hardware for realizing each function may be prepared.

[0033] The first acquisition unit 801 acquires measurement information from the E2 node 104. For example, the first acquisition unit 801 may acquire measurement information such as the communication quality of the RAN, which can be used by the control device 102 to control the RAN, using the O1 interface. The request unit 802 transmits a request message to the processing device 103 to request the provision of the measurement information. The request message may be transmitted using the A1 interface. The request unit 802 may notify the processing device 103 of information specifying the measurement period, provision period, provision procedure, type, unit, etc. of the measurement information, using the request message. In addition, the request unit 802 may notify the processing device 103 of information specifying the method of processing the measurement information, using the request message. The second acquisition unit 803 receives a response message and measurement information from the processing device 103 in response to the request message. If it is possible to provide the measurement information according to the request, the processing device 103 may provide the measurement information together with the response message. Note that the measurement information may be provided in a message separate from the response message. The measurement information obtained by the control device 102 from the E2 node 104 via the first acquisition unit 801 and the measurement information obtained from the processing device 103 via the second acquisition unit 803 may have different information granularity, such as the former being statistical information on a cell basis and the latter being individual information on a UE basis. In addition, the second acquisition unit 803 may also be provided with information such as an analysis result generated independently based on the information acquired by the processing device 103 from the E2 node. The processing process specifying unit 804 specifies processing to be used in the model generation unit 807 or the processing device 103. For example, the processing process specifying unit 804 specifies processing for performing preprocessing when the model generation unit 807 generates a trained model by machine learning. This processing process may also be applied when inference is performed in the processing device 103 using the trained model. As an example, pre-processing specified by the processing specifying unit 804 may be performed on the measurement information acquired by the second acquisition unit 803, thereby acquiring information to be input to machine learning executed by the model generation unit 807. The processing specifying unit 804 specifies one or more processes necessary for the model generation unit 807 to execute machine learning from processing such as normalization, duplicate deletion, and missing value completion.The processing specifying unit 804 may select a processing to be executed from among functions, xApp, and the like shared in advance with the processing device 103. The processing information sharing unit 805 notifies the processing device 103 of the processing specified by the processing information specifying unit 804. The processing information sharing unit 805 may receive a response including a rejection of the notification specifying the processing or a request to change the processing from the processing device 103. The processing information sharing unit 805 may also receive a notification specifying the processing from the processing device 103. Information specifying the processing may be notified to the processing device 103 using a request message. Information specifying the processing may also be notified to the processing device 103 using a method other than the request message. For example, the processing information sharing unit 805 may request the processing device 103 to register a function, xApp, and the like to be used for the processing, and may notify the processing device 103 of the measurement information to be processed, arguments to be used for the function, input parameters to be used for the xApp, and the like, as necessary. The processing unit 806 executes processing on the measurement information. The processing unit 806 may execute the processing using the processing specified by the processing specifying unit 804. The measurement information subjected to the processing may be provided to the model generating unit 807. The model generating unit 807 generates a trained model by machine learning. The model generating unit 807 generates a trained model for performing, for example, future prediction of the communication quality of the RAN. The model generating unit 807 may use the processed measurement information provided by the processing unit 806 as an input for machine learning, or may use the processed measurement information provided by the processing device 103 as an input for machine learning. The model providing unit 808 provides the trained model generated by the model generating unit 807 to the processing device 103. The RAN control unit 809 executes the control of the RAN. As an example, the RAN control unit 809 generates an A1 policy for controlling the RAN using the measurement information acquired by the first acquisition unit 801 and the second acquisition unit 803, and provides the A1 policy to the processing device 103. The RAN control unit 809 can use the measurement information acquired by the second acquisition unit 803 to determine, for example, the achievement status of a performance target for each UE set as an A1 policy, and generate a new A1 policy based on the achievement status. The generated A1 policy can be provided to the processing device 103.

[0034] FIG. 9 is a diagram showing an example of the functional configuration of the processing device 103. The processing device 103 includes, as its functions, an information acquisition unit 901, a storage unit 902, a receiving unit 903, a transmitting unit 904, a processing information sharing unit 905, a processing unit 906, a model acquisition unit 907, and a RAN control unit 908. FIG. 9 shows the functional configuration of the processing device 103 of this embodiment, and, for example, a general configuration of the processing device is omitted. Note that these functional units can be realized, for example, by the processor 701 executing a program stored in the ROM 702 or the storage device 704 and controlling the communication circuit 705 as necessary. However, this is not limited to this, and for example, dedicated hardware for realizing each function may be prepared.

[0035] The information acquisition unit 901 collects measurement information on the RAN from the E2 node 104. The collected information may be, for example, measurement information on communication quality (RSSI, SINR, throughput, delay time, etc.), control function information and control history information of the E2 node, and may be specified on a cell-by-cell, slice-by-slice, UE-by-UE basis. The information acquisition unit 901 may perform analysis using the collected information to generate statistical information, etc. For example, the information acquisition unit 901 may use the measurement information collected from the E2 node to generate statistical values ​​such as the average, maximum, minimum, and variance of the throughput and delay over time of each UE, and the average, maximum, minimum, and variance of the throughput in each cell. In addition, the information acquisition unit 901 may acquire the reception power and interference power in each cell, the resource usage rate of each cell, and the like, and analyze the correlation between each piece of measurement information and each piece of statistical information. Furthermore, the information acquisition unit 901 may acquire and analyze information such as the operation status of each node (including the E2 node) constituting the RAN. The measurement information collected by the information acquisition unit 901 and the analysis results generated may be recorded in the storage unit 902. The storage unit 902 stores the measurement information and analysis results collected from the E2 node 104, the A1 policy, the learned model, the function for processing the measurement information, xApp, and the like received from the control device 102. The reception unit 903 receives a request message requesting the provision of measurement information from the control device 102. The transmission unit 904 determines whether or not to accept the request included in the request message, and transmits a response message to the control device 102. For example, when the transmission unit 904 accepts the request, it transmits the measurement information and the analysis results recorded in the storage unit 902 to the control device 102 according to the request. The measurement information and the analysis results transmitted by the transmission unit 904 may be processed by the processing unit 906. When the transmission unit 904 does not accept the request, it transmits a response message rejecting the request to the control device 102. The response message rejecting the request may include a reason for rejection. The processing information sharing unit 905 can receive information on processing to be used by the processing unit 906 from the control device 102. When executing the processing notified by the control device 102, the processing information sharing unit 905 may transmit a message indicating that the processing is accepted to the control device 102.In addition, when refusing to execute the processing notified by the control device 102, the processing information sharing unit 905 may transmit a message indicating the refusal to the control device 102. In addition, the processing information sharing unit 905 may specify a processing process that the device itself can execute, and transmit a message to the control device 102 requesting that the processing process be changed to the specified processing process. Note that the processing information sharing unit 905 may specify and notify the processing process before the control device 102. The processing unit 906 executes processing of the measurement information and the like stored in the storage unit 902. The measurement information and the like processed by the processing unit 906 may be used for analysis by the RAN control unit 908, and may be provided to the control device 102. The measurement information provided to the control device 102 may be used as an input for machine learning in the control device 102. The model acquisition unit 907 acquires a trained model from the control device 102. The RAN control unit 908 performs an analysis on the RAN using the measurement information, and controls the RAN using the obtained analysis result. The RAN control unit 908 may perform future prediction of the communication quality of the RAN, for example, by using a trained model provided from the control device 102. The RAN control unit 908 may obtain the trained model from a source other than the control device 102. The RAN control unit 908 may analyze the RAN by using a method other than machine learning. For example, the RAN control unit 908 may perform future prediction of the communication quality of the RAN by applying a predetermined analysis algorithm to the measurement information obtained from the E2 node 104. The RAN control unit 908 may configure and operate the RAN by controlling the E2 node 104. The RAN control unit 908 may control the E2 node 104 in accordance with the A1 policy received from the control device 102. The RAN control unit 908 may generate parameters for controlling the E2 node 104, for example, by using the communication quality of the RAN predicted by the analysis.

[0036] In the above, an embodiment has been described as an example in which the processing device 103 collects information measured by an E2 node or the like in the RAN and provides the information to the control device 102, but the information provided to the control device 102 is not limited to such measurement information. The measurement information in this embodiment may also include, for example, information obtained by processing or statistical processing of information measured in a device in the RAN. The measurement information may also broadly include information generated by analysis or the like in each device other than the above, and information on the resource usage status and load of each device.

[0037] As described above, according to this embodiment, the control device 102 requests the processing device 103 to provide the measurement information it has, and the processing device 103 provides the control device 102 with the measurement information in accordance with the request. This measurement information can be used to update the A1 policy in the control device 102 or generate a trained model by machine learning. The control device 102 provides the processing device 103 with an A1 policy updated based on the measurement information or a trained model generated using fine-grained measurement information, and the processing device 103 uses these to control the E2 node 104, thereby making it possible to improve the accuracy of control regarding the setting and operation of the RAN. In addition, according to this embodiment, when the processing device 103 performs inference and controls the RAN using the trained model generated by the control device 102, information that specifies the processing required in each device is shared. This makes it possible to use machine learning that uses measurement information collected from devices constituting the RAN, such as the E2 node, as input in the control of the RAN. This makes it possible to contribute to Goal 9 of the Sustainable Development Goals (SDGs) led by the United Nations, "Build resilient infrastructure, promote sustainable industrialization, and promote innovation."

[0038] The invention is not limited to the above-described embodiment, and various modifications and variations are possible within the scope of the invention. [Explanation of symbols]

[0039] 101: SMO, 102: control device, 103: processing device, 104: E2 node

Claims

1. A control device that functions as a Non-RealTime RAN Intelligent Controller (non-real-time RIC) in an Open-Radio Access Network (O-RAN), a first receiving means for receiving, from an E2 node, first information usable by the non-real-time RIC to control a RAN, the first information being held by the E2 node; a transmission means for transmitting a request message requesting the quasi-real-time RIC to provide second information different from the first information, the second information including information collected by the quasi-real-time RIC from the E2 node or information generated by the quasi-real-time RIC, the second information being usable by the non-real-time RIC to control a RAN; A second receiving means for receiving the second information transmitted from the near real-time RIC; and a control means for controlling a RAN using the first information and the second information. A control device comprising:

2. The second receiving means receives a response message indicating whether the second information can be provided from the near real-time RIC in response to the request message, and receives the second information in the response message indicating acceptance of the provision of the second information or in a message separate from the response message. The control device according to claim 1 .

3. The request message includes at least one of information indicating which of a procedure in which the second information is periodically provided from the near real-time RIC and a procedure in which the second information collected over a predetermined period in the near real-time RIC is collectively provided, should be used, and information indicating a period in which the second information is to be provided from the near real-time RIC. The control device according to claim 1 .

4. The request message includes information specifying a type of information to be provided as the second information. The control device according to claim 1 .

5. The information for identifying the type is information for specifying one or more of data defined in an existing standard, newly defined data, and data defined independently by a vendor.

5. The control device according to claim 4.

6. The request message includes information that specifies one or more units of a cell unit, a terminal unit, a terminal group unit, a slice unit, or a QoS unit as a unit of information to be provided as the second information. The control device according to claim 1 .

7. A processing device that functions as a Near-RealTime RAN Intelligent Controller (Near-real-time RIC) in an Open-Radio Access Network (O-RAN), a receiving means for receiving from the non-real-time RIC a request message for requesting provision of second information that is different from first information that the non-real-time RIC can receive from an E2 node, the second information including information collected by the quasi-real-time RIC from the E2 node or information generated by the quasi-real-time RIC and that the non-real-time RIC can use to control a RAN; A transmitting means for providing the second information to the non-real-time RIC; A processing device comprising:

8. The transmitting means transmits a response message notifying whether the second information can be provided in response to the request message, and transmits the second information in the response message indicating that the second information can be provided or in a message separate from the response message.

8. The processing device according to claim 7 .

9. 8. The processing device according to claim 7, wherein the request message includes at least one of information indicating which procedure should be used, a procedure of periodically providing the second information to the non-real-time RIC or a procedure of providing the second information collected over a predetermined period in a lump sum, and information indicating a period during which the second information should be provided to the non-real-time RIC.

10. The request message includes information specifying a type of information to be provided as the second information.

8. The processing device according to claim 7 .

11. The information for identifying the type is information for specifying one or more of data defined in an existing standard, newly defined data, and data defined independently by a vendor. The processing device according to claim 10 .

12. The request message includes information that specifies one or more units of a cell unit, a terminal unit, a terminal group unit, a slice unit, or a QoS unit as a unit of information to be provided as the second information.

8. The processing device according to claim 7 .

13. A control method executed by a control device functioning as a Non-RealTime RAN Intelligent Controller (non-real-time RIC) in an Open-Radio Access Network (O-RAN), comprising: a first receiving step of receiving, from an E2 node, first information usable by the non-real-time RIC to control a RAN, the first information being held by the E2 node; a sending step of sending a request message to the quasi-real-time RIC to request provision of second information, different from the first information, the second information including information collected by the quasi-real-time RIC from the E2 node or information generated by the quasi-real-time RIC, the second information usable by the non-real-time RIC to control the RAN; a second receiving step of receiving the second information transmitted from the near real-time RIC; and a control step of controlling a RAN using the first information and the second information. A control method comprising:

14. A processing method executed by a processing device functioning as a Near-RealTime RAN Intelligent Controller (Near-RealTime RIC) in an Open-Radio Access Network (O-RAN), comprising: receiving a request message from the non-real-time RIC requesting provision of second information that is different from first information that the non-real-time RIC can receive from an E2 node, the second information including information collected by the non-real-time RIC from the E2 node or information generated by the non-real-time RIC, and that the non-real-time RIC can use to control the RAN; a transmitting step of providing the second information to the non-real-time RIC; A processing method comprising the steps of:

15. A computer provided in a control device that functions as a Non-RealTime RAN Intelligent Controller (non-real-time RIC) in an Open-Radio Access Network (O-RAN), receiving, from an E2 node, first information usable by the non-real-time RIC to control a RAN, the first information held by the E2 node; causing the non-real-time RIC to transmit a request message requesting the quasi-real-time RIC to provide second information different from the first information, the second information including information collected by the quasi-real-time RIC from the E2 node or information generated by the quasi-real-time RIC, the second information usable by the non-real-time RIC to control the RAN; receiving the second information transmitted from the near real-time RIC; Controlling the RAN using the first information and the second information. Program for.

16. A computer equipped with a processing device functioning as a Near-Real-Time RAN Intelligent Controller (quasi-real-time RIC) in an Open-Radio Access Network (O-RAN), receiving from the non-real-time RIC a request message requesting provision of second information, the second information being different from first information receivable by the non-real-time RIC from an E2 node, the second information including information collected by the non-real-time RIC from the E2 node or information generated by the non-real-time RIC and usable by the non-real-time RIC to control the RAN; causing the non-real-time RIC to provide the second information; Program for.

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