Network optimization method, server, network side device, system and storage medium

Abstract

The present application proposes a network optimization method, a server, a network side device, a system and a storage medium, the method comprising: determining network side measurement control information according to pre-acquired policy information that the network needs to meet; sending a session establishment request to a specified network side device to request the specified network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on a terminal device connected to the specified network side device; receiving a measurement report of the specified network side device and a measurement report of the terminal device; performing machine learning for network optimization based on the measurement data and policy information in the received measurement report to obtain a network optimization operation instruction, the network optimization operation instruction being used to instruct the specified network side device and the terminal device to perform network optimization according to the network optimization operation instruction.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a network optimization method, a server, a network-side device, a system and a storage medium. Background Art

[0002] The fifth generation wireless communication network (The 5th Generation Wireless Systems Network) is currently being deployed, and is expected to develop beyond 5G (Beyond 5G, B5G) networks in the future.

[0003] When optimizing a network, there is no network intelligence solution for configuring artificial intelligence (AI) functions on the communication network to perform network intelligent optimization processes based on AI. Summary of the invention

[0004] The present application provides a method, server, network-side device, system and storage medium for network optimization.

[0005] In a first aspect, an embodiment of the present application provides a network optimization method, including: determining network side measurement control information based on pre-acquired policy information that the network needs to meet; sending a session establishment request to a specified network side device to request the specified network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on a terminal device connected to the specified network side device; receiving a measurement report from the specified network side device and a measurement report from the terminal device; performing machine learning for network optimization based on the measurement data and policy information in the received measurement report to obtain a network optimization operation instruction, the network optimization operation instruction being used to instruct the specified network side device and the terminal device to perform network optimization according to the network optimization operation instruction.

[0006] In a second aspect, an embodiment of the present application provides a network optimization method, comprising: in response to receiving a session establishment request from a predetermined server, performing measurement configuration according to network side measurement control information in the session establishment request and performing measurement configuration on a terminal device connected to a specified network side device; sending the measurement report of the current network side device and the received measurement report of the terminal device to the predetermined server, and the measurement report of the current network side device and the measurement report of the terminal device are used in the predetermined server for machine learning for network optimization.

[0007] In a third aspect, an embodiment of the present application provides a server, comprising: a measurement control information determination module, used to determine network side measurement control information based on pre-acquired policy information that the network needs to meet; a measurement configuration request module, used to send a session establishment request to a specified network side device to request the specified network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on a terminal device connected to the specified network side device; a measurement report receiving module, used to receive measurement reports from specified network side devices and measurement reports from terminal devices; a machine learning module, used to perform machine learning for network optimization based on measurement data and policy information in the received measurement reports to obtain network optimization operation instructions, the network optimization operation instructions being used to instruct the specified network side device and terminal device to perform network optimization according to the network optimization operation instructions.

[0008] In a fourth aspect, an embodiment of the present application provides a network side device, comprising: a measurement configuration module, used to respond to a session establishment request received from a predetermined server, perform measurement configuration according to the network side measurement control information in the session establishment request and perform measurement configuration on a terminal device connected to a specified network side device; a measurement report sending module, used to send the measurement report of the current network side device and the measurement report of the received terminal device to the predetermined server, and the measurement report of the current network side device and the measurement report of the terminal device are used in the predetermined server to perform machine learning for network optimization.

[0009] In the fifth aspect, an embodiment of the present application provides a server, comprising: one or more first processors; a memory, on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the network optimization method of the above-mentioned first aspect in the embodiment of the present application.

[0010] In the sixth aspect, an embodiment of the present application provides a network side device, including: one or more second processors; a memory, on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the network optimization method of the above-mentioned second aspect in the embodiment of the present application.

[0011] In the seventh aspect, an embodiment of the present application provides a network side device, a network optimization system, including: a server, the server is used to execute the network optimization method of the first aspect mentioned above; one or more network side devices, the network side devices are used to execute the network optimization method of the second aspect mentioned above.

[0012] In an eighth aspect, an embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the network optimization method of any aspect in the embodiment of the present application is implemented.

[0013] According to the network optimization method, server, network-side device, system and storage medium in the embodiments of the present application, network-side measurement control information can be determined based on pre-acquired policy information that the network needs to meet, and the network-side device can be requested to perform measurement configuration and terminal-side measurement configuration according to the network-side measurement control information, and the measurement data received from the wireless network side and terminal side measurements are used for machine learning model training to obtain network optimization operations, thereby performing in-depth analysis of the collected data through artificial intelligence and machine learning in the network system, providing a new optimization method and network intelligent optimization process for operator network optimization.

[0014] According to the network optimization method, server, network side device, system and storage medium in the embodiments of the present application, measurement configuration can be performed according to the received network side measurement control information and measurement configuration can be performed on the connected terminal device, and the measurement report obtained by performing the measurement and the measurement report of the received terminal side device can be sent to a predetermined server. The measurement report of the network side device and the measurement report of the terminal device are used in the AI ​​server to perform machine learning for network optimization, so that the data collected by the network side device and the terminal device can be deeply analyzed in artificial intelligence and machine learning, providing new optimization methods and network intelligent optimization processes for operator network optimization.

[0015] With regard to the above embodiments and other aspects of the present application and their implementation, further description is provided in the accompanying drawings, detailed description and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart showing a network optimization method according to an embodiment of the present application is shown.

[0017] Figure 2 A flow chart of a network optimization method according to another embodiment of the present application is shown.

[0018] Figure 3 A schematic diagram showing a timing flow of a network optimization method according to an embodiment of the present invention is shown.

[0019] Figure 4 A schematic diagram showing a timing flow of a network optimization method according to another embodiment is shown.

[0020] Figure 5 A schematic diagram of a process for establishing a communication interface between a server and a network-side device according to an embodiment is shown.

[0021] Figure 6 A schematic diagram showing a flow chart of establishing a data channel related to a predetermined server and a user device according to an embodiment.

[0022] Figure 7A schematic diagram showing the structure of a server provided by an embodiment of the present invention is shown.

[0023] Figure 8 A schematic structural diagram of a network side device provided by an embodiment of the present invention is shown.

[0024] Fig. 9 A schematic diagram showing the structure of a network optimization system provided by an embodiment of the present invention is shown.

[0025] Fig.10 is a block diagram showing an exemplary hardware architecture capable of implementing a computing device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present application more clear, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other arbitrarily without conflict.

[0027] In the embodiments of the present application, while 5G networks bring fundamental changes in performance and flexibility, the complexity of network operations is also significantly improved. Operators urgently need automation and intelligent means to reduce network deployment and operation and maintenance costs and improve network performance and user experience. Self-organizing network technologies in LTE and 5G, such as Self-Organized Network (SON) and Minimization of Drive Tests (MDT), play a great role in network optimization, but have not achieved the goal of flexible intelligent networks. 5G networks face the challenge of joint optimization of many network key performance indicators (KPIs). These indicators include, for example, latency, reliability, connection density, user experience, etc.

[0028] Traditional network optimization methods are increasingly showing problems such as long response cycles, prone to errors, and high costs. The measurements in the node devices and terminal devices of the Radio Access Network (Remote Asynchronous Node, RAN) can be used by the network management system to monitor network KPIs, and can also assist network vendors in optimizing wireless resource management. However, there is no solution for how the network elements where the AI ​​functions are located collect these measurements. The embodiment of the present application provides a network optimization solution that uses artificial intelligence / machine learning to deeply analyze the collected data, provides a new network optimization method for operator network optimization, and supports AI-based network intelligent optimization processes in the existing network architecture.

[0029] Figure 1A schematic diagram of a flow chart of a network optimization method according to an embodiment of the present application is shown. In one embodiment, the network optimization method according to the embodiment of the present application can be applied to an AI server, such as Figure 1 As shown, the network optimization method includes the following steps.

[0030] S110: Determine network-side measurement control information according to pre-acquired policy information that needs to be satisfied by the network.

[0031] S120, sending a session establishment request to a designated network side device to request the designated network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on a terminal device connected to the designated network side device.

[0032] S130, receiving a measurement report of a designated network side device and a measurement report of a terminal device.

[0033] S140, based on the measurement data and policy information in the received measurement report, perform machine learning for network optimization to obtain network optimization operation instructions, where the network optimization operation instructions are used to instruct designated network-side devices and terminal devices to perform network optimization according to the network optimization operation instructions.

[0034] According to the network optimization method of the embodiment of the present application, the AI ​​server can configure measurements on the wireless network side and the terminal side according to the policy information that the network needs to meet, and receive measurement data of the wireless network side and the terminal side. The received measurement data is used for machine learning model training to obtain network optimization operations, thereby performing in-depth analysis of the collected data through artificial intelligence and machine learning in the network system, providing a new optimization method for operator network optimization and supporting AI-based network intelligent optimization processes.

[0035] In the description of the embodiments of the present application, the network side device may be, for example, a RAN node device in a 5G network or a beyond 5G (B5G) network. As an example, the RAN node device includes but is not limited to a base station.

[0036] In one embodiment, before step S110, the method further includes: S01, obtaining policy information that a pre-configured network needs to satisfy; or, S02, activating a machine learning function in response to a received activation message, and obtaining policy information that the network needs to satisfy carried in the activation message.

[0037] In this embodiment, the policy information that the network needs to meet can be pre-configured directly on the AI ​​server, or obtained from an activation message received from the network management and maintenance system (Operation Administration And Maintenance, OAM) or the core network. The policy information that the network needs to meet is relatively flexible and can be set according to actual needs.

[0038] Exemplarily, the received activation message may include an indication of whether the machine learning function is activated, and the machine learning function is activated or disabled according to the indication. After the machine learning function is activated, the policy information (Policy Information) that needs to be met by the network side carried in the message is obtained.

[0039] In one embodiment, the policy information may include object identification information and communication quality indicator information.

[0040] In this embodiment, the above step S110 may include the following steps S111 and S112.

[0041] S111 , determining, according to the entity identified by the object identification information, a network side device that needs to perform measurement as a designated network side device.

[0042] In one embodiment, the policy information that the network needs to meet includes one or more of the following object identification information: one or more terminal equipment identifications (User Equipment Identity, UE ID), one or more service quality business flow identifications (QOS FLOW Identity, QFI) identifications, one or more cell identifications, one or more network slice identifications, one or more public network identifications (Public Land Mobile Network, PLMN Identity), one or more private network identifications, one or more base station identifications, and one or more tracking area identifications (Tracking Area Code Identity, TAC ID).

[0043] In this embodiment, if the entity identified by the object identification information is one or more terminal devices, the network side device that needs to perform measurement may be the network side device to which the identified terminal device is connected; if the entity identified by the object identification information is at least one of one or more quality of service business flows, one or more cells, one or more network slices, one or more public networks, and one or more private networks, the network side device that needs to perform measurement may be the network side device involved in the communication range of the identified entity.

[0044] In this embodiment, the network side device that needs to perform measurement can also be flexibly selected according to the actual requirements of machine learning, and the embodiment of the present application does not make specific limitations.

[0045] S112, according to the communication quality that the entity needs to achieve as indicated by the communication quality indicator information, determine the measurement quantity and measurement reporting method that the specified network side device needs to be configured with as network side measurement control information.

[0046] In one embodiment, the communication quality indicator information may be used to indicate the communication quality required to be achieved by the entity identified by the corresponding object identification information. Exemplarily, the communication quality indicator information may include one or more of the following indicator items: network energy saving indicator, network KPI, service quality indicator (Quality of Service), user experience quality indicator (Quality of Experience, QOE), service perception quality indicator (Key Quality Indicators, KQI) and service diversion indicator (Traffic Steering Preferences).

[0047] Exemplarily, the network energy saving index may include, for example, one or more of: energy saving efficiency, energy saving percentage index, and energy saving value.

[0048] As an example, the network KPI may include one or more of: handover success rate, call drop rate, access success rate, user throughput rate, cell throughput rate, cell load, network load, wireless resource utilization rate, and network coverage rate.

[0049] As an example, the service quality indicator may include one or more of: service guaranteed rate, service maximum / minimum rate, service delay, service priority, delay jitter, and packet loss rate.

[0050] As an example, the user experience quality indicator may include: a mean opinion score (MOS) for measuring the voice quality of the communication system, a streaming media open cache time, a streaming media re-caching time, and one or more of the streaming media re-caching times.

[0051] Through the above steps S111-S112, the AI ​​server can instruct the network side device to perform measurement configuration and configure the terminal device according to the pre-acquired policy information that the network needs to meet.

[0052] In the description of the embodiments of the present application, the network management and maintenance system may be referred to as the network management system, and the core network may be, for example, the fifth generation mobile communication technology core network (The 5th Generation Wireless Systems Core Network) 5GC, or the core network of a communication network exceeding 5G.

[0053] In one embodiment, the deployment location of the current server includes outside the network side device and inside the network side device; S120 may specifically include the following steps.

[0054] S121: If the deployment location of the current server is outside the network side device, a session establishment request message is sent to the specified network side device, where the session establishment request message includes network side measurement control information.

[0055] S122, if the deployment location of the current server is inside the network side device, perform measurement configuration on the network side device where the current server is located according to the network side measurement control information, and send a session establishment request message to the specified network side device, wherein the session establishment request message includes the network side measurement control information.

[0056] In this embodiment, if the deployment location of the AI ​​server is inside the network side device, the network side device where the AI ​​server is deployed also needs to perform measurement configuration according to the network side measurement control information. If the deployment location of the AI ​​server is outside, the AI ​​server can send a machine learning session setup request message (Machine Learning Session SetupRequest) or a session setup request message to the network side device to instruct the network side device to perform measurement configuration according to the network side measurement control information and perform measurement configuration on the terminal device connected to the specified network side device.

[0057] In one embodiment, the session establishment request carries a machine learning session identifier and network-side measurement control information, wherein each machine learning session identifier is used to uniquely identify a machine learning process, and the network-side measurement control information is used to indicate the measurement quantity to be collected and the measurement reporting method for the uniquely identified machine learning process.

[0058] In another embodiment, the session establishment request carries network side measurement control information, wherein the carried network side measurement control information is used to indicate the measurement quantity to be collected and the measurement reporting method for all machine learning processes.

[0059] That is to say, the session establishment request carries the network side measurement control information. Optionally, it may also carry a machine learning session ID. The machine learning session ID can be used to uniquely identify a machine learning process. If the session establishment request does not contain the machine learning session ID, it indicates that the measurement control information in the session establishment request is for all ML processes.

[0060] In an embodiment of the present application, a machine learning process can be used to represent the machine learning corresponding to the network-side measurement control information carried in the session establishment request. Exemplarily, the machine learning process can be determined according to different optimization indicators, such as setting different optimization indicators for different communication quality indicators, and different optimization indicators correspond to different machine learning processes; or, the machine learning process can be determined by the machine learning type, and the machine learning type includes but is not limited to any one of supervised learning, unsupervised learning, reinforcement learning, deep learning, and transfer learning; or, the machine learning process can be determined by a machine learning model, and the machine learning model includes but is not limited to any one of: convolutional neural network, recurrent neural network, long short-term memory network, support vector machine, autoregressive moving average model, and decision tree.

[0061] In one embodiment, after the above step S120, the method further includes: in response to the received session establishment response message, determining that both the specified network side device and the terminal device have successfully measured the configuration.

[0062] In this embodiment, if the measurement configuration of the network side device and the measurement configuration of the terminal device are both configured successfully, the network side device can send a session establishment response message to the AI ​​server, wherein the session establishment response message carries a session establishment success indication; or, it can carry a session establishment success indication and a learning session identifier (ML session ID).

[0063] In one embodiment, if the measurement configuration of the network side device fails or the measurement configuration of the terminal device fails, the network side device sends a machine learning session establishment response message to the AI ​​server, wherein the message carries a session establishment failure indication. The session establishment response message may carry a session identifier, and the AI ​​resends the session establishment request upon receiving the failure indication.

[0064] In one embodiment, the session establishment request, the session establishment response message and the received measurement report include a corresponding machine learning session identifier, and the machine learning session identifier is used to uniquely identify the machine learning process.

[0065] In one embodiment, step S130 may include the following steps.

[0066] S131, receiving a measurement report of a designated network side device and a measurement report of a terminal device sent by the designated network side device.

[0067] In this embodiment, the AI ​​server is not directly connected to the terminal device. After the terminal device reports the measurement report to the network side device, the network side device reports the measurement report of the terminal device. The AI ​​server can obtain the measurement report of the terminal device through the communication interface between the AI ​​server and the network side device.

[0068] In one embodiment, the measurement data in the received measurement report includes the collected measurement quantity and the machine learning session identifier, wherein the machine learning session identifier is used to uniquely identify the machine learning process.

[0069] In this embodiment, the network side device sends a measurement report message to the AI ​​server, and the measurement report message sent by the terminal device may carry the measurement amount; or, may carry the measurement amount and the session identifier at the same time.

[0070] In one embodiment, after step S140, the method further includes: sending a network operation request message to a specified network side device, wherein the network operation request message includes a network optimization operation instruction and corresponding operation parameters.

[0071] In this embodiment, the AI ​​server may notify the network side device to perform relevant optimization operations (Action) through a network operation request message (Action Request), wherein the optimization operation action may be one or more operation indications and parameters required for the corresponding operation, such as but not limited to: UE switching indication, cell closing / opening indication, wireless resource activation / deactivation indication, power adjustment indication, RRM parameter reconfiguration indication, offloading operation indication, protocol layer parameter reconfiguration indication, etc.

[0072] In one embodiment, the current server communicates with the designated network side device through a predetermined interface. Before step S120, the method further includes the following steps.

[0073] S11, if the deployment location of the current server is outside the network side device, then in response to the received control plane interface establishment request message, establish a control plane interface between the current server and the specified network side device as a predetermined interface;

[0074] S12, if the deployment location of the current server is inside the network side device, then obtain the existing communication transmission interface between the network side device where the current server is located and the specified network side device as the predetermined interface.

[0075] In this embodiment, the communication interface between the AI ​​server and the network side device can be predetermined based on the current deployment location of the server before measuring and configuring the network side device and the terminal device.

[0076] When the deployment location of the AI ​​server is outside the specified network-side device, the AI ​​server can respond to the interface establishment request of the network-side device and establish a control plane interface with the network-side device; when the deployment location of the AI ​​server is inside the specified network-side device, the existing communication transmission interface between the network-side devices can be used directly for communication, without the need to establish an additional communication interface between the AI ​​server and the network-side device, saving network resources. The interface between the network-side devices. As an example, 5G network-side devices (such as base stations) can be connected through the core network, and the base station and the core network can communicate through optical fiber transmission. As an example, 5G network-side devices can also be connected through wired connections, wireless connections, wireless relays, etc., which are not specifically limited in the embodiments of the present application.

[0077] In one embodiment, the control plane interface establishment request message includes one or more of the following information items: measurements supported by the specified network side device, reporting methods supported by the specified network side device, network optimization operations supported by the specified network side device, and the data plane channel address of the specified network side device.

[0078] In one embodiment, when the AI ​​server sends a session establishment request to a specified network side measurement device, it can obtain network side measurement control information based on the measurements supported by the specified network side device and the reporting methods supported by the specified network side device, so that the measurement configuration of the network side device is more targeted. The measurement of the network side device is configured according to the supported measurements and the reporting methods supported by the specified network side device, which can improve the processing efficiency and accuracy of the measurement configuration.

[0079] In one embodiment, the AI ​​server sends a network operation request message to a specified network side device. The network operation request message may include network optimization operation instructions and corresponding operation parameters that can be supported by the network side measurement device, thereby improving the efficiency and accuracy of the specified network optimization operation instructions.

[0080] In one embodiment, after step S11, the method also includes: S21, sending a control plane interface establishment response message to a specified network side device to indicate that the control plane interface is successfully established; S22, if the control plane interface establishment request message includes the data plane channel address of the specified network side device, then when sending the control plane interface establishment response message to the specified network side device, the data plane channel address of the current server is carried in the control plane interface establishment response message.

[0081] In this embodiment, if the interface establishment request received by the AI ​​server carries the data plane channel address of the network side device, the data plane channel address of the AI ​​server side can be carried in the interface establishment response message to establish the data plane channel with the specified network side device.

[0082] In an embodiment of the present application, control messages required for machine learning can be transmitted between the AI ​​server and the network side device on the control plane channel. The control plane data may include, for example: network side measurement configuration information, sending session establishment request, receiving session establishment response, sending network operation request, receiving network operation response, etc. It can also be used to receive measurement data of network side devices, measurement data of terminal devices, etc.

[0083] In order to improve data transmission efficiency and not affect the transmission of control messages in the control plane channel between the AI ​​server and the network side device when the amount of measurement data of the terminal device is large, a data plane channel can be established between the AI ​​server and the network side device to transmit the data required for machine learning.

[0084] It should be understood that data with a relatively large amount of data can be transmitted on the data plane channel, such as measurement data of a base station. However, the data plane channel established in this embodiment is not limited to transmitting measurement data from a designated terminal device.

[0085] According to the network optimization method provided in the embodiment of the present application, the AI ​​server can configure and receive the measurement data of the wireless network side and the measurement data measured on the terminal side, perform machine learning model training, and obtain network optimization operations, thereby performing in-depth analysis of the collected data through artificial intelligence and machine learning, and using intelligent network optimization methods to provide new optimization methods for operator network optimization and support AI-based network intelligent optimization processes.

[0086] Figure 2 A flow chart of a network optimization method according to another embodiment of the present application is shown. In one embodiment, the network optimization method is applied to a network side device, such as Figure 2 As shown, the network optimization method may include the following steps.

[0087] S210 , in response to receiving a session establishment request from a predetermined server, performing measurement configuration according to network-side measurement control information in the session establishment request and performing measurement configuration on a terminal device connected to a designated network-side device.

[0088] S220, sending the measurement report of the current network side device and the measurement report of the received terminal device to the predetermined server. The measurement report of the current network side device and the measurement report of the terminal device are used in the predetermined server for machine learning for network optimization.

[0089] According to the network optimization method of the embodiment of the present application, the network side device can perform measurement configuration based on the received network side measurement control information and perform measurement configuration on the connected terminal device, and send the measurement report obtained by the measurement and the measurement report of the received terminal side device to a predetermined server. The measurement report of the network side device and the measurement report of the terminal device are used in the AI ​​server to perform machine learning for network optimization, so that the data collected by the network side device and the terminal device can be deeply analyzed in artificial intelligence and machine learning, providing new optimization methods and network intelligent optimization processes for operator network optimization.

[0090] In one embodiment, S210 may specifically include the following steps.

[0091] S211, in response to the session establishment request, performing measurement configuration according to the network side measurement control information, where the network side measurement control information is used to indicate the measurement amount and measurement reporting method that the current network side device needs to configure;

[0092] S212, determining, according to the network side measurement control information, a measurement quantity and a measurement reporting method that need to be configured for the terminal device connected to the current network side device as the terminal side measurement control information;

[0093] S213: Send a first wireless resource control message to the terminal device to instruct the terminal device to perform measurement configuration according to the terminal side measurement control information.

[0094] In this embodiment, the network side device can perform network side measurement configuration according to the network side measurement control information carried in the session establishment request from the AI ​​server, and instruct the connected terminal device to perform terminal side measurement configuration.

[0095] In one embodiment, if the current network side device measurement configuration is successful and a measurement configuration response message of the terminal device is received, a session establishment response message is sent to the predetermined server to feedback to the predetermined server that the current network side device and the terminal device are both successfully measured and configured.

[0096] In one embodiment, the received session establishment request, session establishment response message, and measurement report sent to the predetermined server include a corresponding machine learning session identifier, and the machine learning session identifier is used to uniquely identify the machine learning process.

[0097] In one embodiment, the network side optimization method also includes: S240, receiving and executing network optimization operation instructions from a predetermined server; S241, if the network optimization operation instructions involve a terminal device, determining the operations related to the terminal device in the network optimization operation instructions; S242, sending a second wireless resource control message to the terminal device to instruct the terminal device to perform related operations.

[0098] Through steps S240 and S242, the network side device executes the received network optimization operation instruction. If the network optimization operation instruction involves a terminal device, the network optimization operation instruction is sent to the terminal device involved, thereby performing optimization operations on the network side and the terminal side to achieve network optimization according to the network optimization operation instruction.

[0099] In one embodiment, the current network side device communicates with the predetermined server through a predetermined interface, and before step S210, the method may further include the following steps.

[0100] S31, if the deployment location of the predetermined server is outside the current network side device, then according to the address of the predetermined server obtained in advance, a control plane interface establishment request message is sent to the predetermined server to request the predetermined server to establish a control plane interface between the current network side device and the predetermined server as the predetermined interface.

[0101] S41, if the deployment location of the predetermined server is inside the current network side device, then obtain the existing communication transmission interface between the current network side device and the network side device where the predetermined server is located as the predetermined interface.

[0102] Through the above steps S31 and S41, the establishment of the control panel interface communication interface between the current network side device and the predetermined server can be achieved.

[0103] In one embodiment, the control plane interface establishment request message includes one or more of the following information items: measurements supported by the current network side device, reporting methods supported by the current network side device, network optimization operations supported by the current network side device, and the data plane channel address of the current network side device.

[0104] In this embodiment, the control plane interface establishment request message can be used to request a predetermined server to send network side measurement configuration information that can be supported by the current network side device based on the measurements supported by the current network side device and the reporting methods supported by the current network side device, thereby improving the success rate and processing efficiency of the network side measurement configuration.

[0105] In this embodiment, the control plane interface establishment request message can also be used to request a predetermined server to send network optimization operation instructions that can be supported by the current network side device based on the network optimization operations supported by the current network side device, so as to perform network optimization based on the received network optimization operation instructions that can be supported, thereby improving the data processing performance of the network side in measuring and executing network optimization operation instructions.

[0106] In one embodiment, the network optimization method also includes: S250, in response to a received control plane interface establishment response message, determining that the control plane interface between the current network side device and the predetermined server is successfully established; wherein, if the control plane interface establishment request message includes the data plane channel address of the current network side device, then the received control plane interface establishment response message includes the data plane channel address of the predetermined server.

[0107] In this embodiment, the network side device can send an interface establishment request based on the received address of the AI ​​server to request to establish a control plane interface between the network side device and the AI ​​server. The interface establishment request can carry one or more of the following: measurements supported by the network side device; reporting methods of measurements supported by the network side device; RAN optimization operations supported by the network side device; and data plane channel address of the network side device.

[0108] When the interface establishment request carries the data plane channel address of the network side device, a data plane interface between the network side device and the AI ​​server is established in response to the data plane channel address of the AI ​​server carried in the interface establishment response. Data can be transmitted between the network side device and the AI ​​server using the control plane interface and / or the data plane interface as needed.

[0109] According to the network optimization method of the embodiment of the present application, the network side device can, under the control of the AI ​​server, perform measurement configuration on the network side device and the terminal device, and can send the measurement data obtained by the network side device and the measurement data obtained by the terminal device to the AI ​​server for performing machine learning for network optimization on the AI ​​server, thereby receiving and executing the network optimization operation instructions obtained by machine learning to perform network optimization.

[0110] In order to better understand this application, Figure 3 and Figure 4 , describe in detail the network optimization method of the embodiment of the present application. Figure 3 FIG. 1 is a schematic diagram showing a timing diagram of a network optimization method according to an embodiment of the present invention. Figure 3 As shown, the AI ​​server is arranged outside the network side device, and the network optimization method may include the following steps.

[0111] S301, the network management system or the core network sends an activation message through the interface with the AI ​​server.

[0112] In this step, OAM or 5GC sends an activation message to instruct the AI ​​server to activate or use the machine learning function. The message includes an indication of whether the ML function is activated; the message includes policy information that indicates the RAN network side needs to meet.

[0113] S302, the AI ​​server sends a machine learning session establishment request message to the RAN node device to configure the wireless side measurement data required for a machine learning session.

[0114] In this step, the machine learning session establishment request message may include a machine learning session ID to uniquely identify the ID of a certain ML process, and the measurement control information is used to indicate the measurement quantity and measurement reporting method that the RAN node device needs to measure. If the machine learning session establishment request message does not include a session ID, it indicates that the measurement control in the request message is for all ML processes.

[0115] S303: The RAN node device configures the measurement and reporting method that the RAN node device needs to perform according to the measurement control information in the received message.

[0116] S304, the RAN node device configures the measurement control information on the terminal side according to the measurement control information in the received message, and sends the measurement control information on the UE side to one or more UEs connected to the RAN node device through an RRC establishment / reconfiguration message, instructing the UE which measurements to make and how to report.

[0117] S305, if the RAN node device measurement and the UE side measurement are configured successfully, the RAN node device sends a machine learning session establishment response message to the AI ​​server, wherein the message carries a success indication, and the message optionally carries a machine learning session ID (MLsession ID). If the RAN node device measurement or the UE side measurement configuration fails, the RAN node device sends a machine learning session establishment response message to the AI ​​server, wherein the message carries a failure indication, and the message optionally carries a machine learning session ID (ML session ID).

[0118] S306: If the RAN node device measurement and the UE side measurement are configured successfully, the RAN node device and the UE perform relevant measurements according to the specified measurement configuration.

[0119] S307-01, the RAN node device sends a measurement report to the AI ​​server.

[0120] S307-02, the RAN node device sends the measurement report received from the terminal.

[0121] In this step, the measurement report message may carry the measurement amount, or may carry the measurement amount and the machine learning session ID to which the measurement belongs.

[0122] S308, the AI ​​server selects a suitable ML algorithm for model training, model prediction, and model update based on the measurement data and the configured policy information, and derives the RAN operations required for optimization.

[0123] S308: The AI ​​server notifies the RAN node to perform relevant optimization operations through a RAN operation request message.

[0124] S310, the RAN node device executes relevant optimization operations in the RAN operation request message.

[0125] S311, the RAN node device sends an RRC reconfiguration message or an RRC release message to the UE connected to the RAN node device, informing the UE to perform related operations.

[0126] Through the network optimization method in this embodiment, after the machine learning function of the AI ​​server is activated, the RAN node device is measured and configured, and the terminal device connected to the RAN node device is measured and configured through the RAN node device. The RAN node device and the terminal device perform measurements and send measurement reports to the AI ​​server; the AI ​​server selects a suitable ML algorithm for model training, model prediction, and model update based on the measurement data and the configured policy information, obtains and sends the RAN operations required for optimization, thereby performing network optimization by optimizing the required RAN operations.

[0127] Figure 4 FIG. 2 is a schematic diagram showing a timing diagram of a network optimization method according to another embodiment of the present invention. Figure 4 As shown, the AI ​​server is arranged inside the network side device, and the network optimization method may include the following steps.

[0128] S401, the network management system or the core network sends an activation message through the interface with the AI ​​server.

[0129] S402, the AI ​​server configures the measurements required by the RAN node device 1.

[0130] S403, RAN node device 1 configures measurement control information on the terminal device side.

[0131] In this step, the RAN node device 1 sends an RRC establishment / reconfiguration message carrying the terminal device side measurement control information to one or more terminal devices connected to the RAN node device 1, instructing the terminal devices which measurements to make and how to report.

[0132] S404, the AI ​​server sends a machine learning session establishment request message to the RAN node device 2, which is used to configure the wireless side measurement data required for a machine learning session.

[0133] S405 , the RAN node device 2 configures the measurement quantity that the RAN node device 2 needs to measure and the measurement reporting method according to the measurement control information in the received message.

[0134] S406, RAN node device 2 configures measurement control information on the terminal device side according to the measurement control information in the received message.

[0135] In this step, the RAN node device 2 may carry the terminal device side measurement control information through an RRC establishment / reconfiguration message and send it to one or more terminal devices connected to the base station, instructing the terminal devices which measurements to make and how to report.

[0136] S407: If the measurement on the RAN node device 2 side and the measurement on the terminal device side are configured successfully, the base station sends a machine learning session establishment response message to the RAN node device 1.

[0137] The message carries a success indication, and optionally carries a machine learning session ID (machine learning sessionID). If the measurement on the RAN node device 2 side or the measurement configuration on the terminal device side fails, the RAN node device 2 sends a machine learning session establishment response message to the RAN node device 1, wherein the message carries a failure indication, and optionally carries a machine learning session ID (machine learning sessionID).

[0138] S408, if the measurement on the RAN node device 2 side and the measurement on the terminal device side are configured successfully, the RAN node device 2 and the terminal device both perform relevant measurements according to the specified measurement configuration. At the same time, the RAN node device 1 also performs relevant measurements according to the measurement configured by the AI ​​server.

[0139] S409, RAN node device 1 receives the measurement report.

[0140] In this step, the measurement report may be sent directly from the terminal device connected to the RAN node device 1 to the RAN node device 1 (corresponding to step S409-02), the measurement report may be a measurement made on the RAN node device 2 and sent to the RAN node device 1 (corresponding to step S409-01), and the measurement report may be sent from the terminal device connected to the RAN node device 2 to the RAN node device 2 and forwarded to the RAN node device 1 by the RAN node device 2 (corresponding to step S409-03).

[0141] S410, the AI ​​server selects a suitable machine learning algorithm for model training, model prediction, and model update based on the measurement data and the configured policy information, and derives the RAN operations required for optimization.

[0142] S411, the AI ​​server notifies the RAN node device 1 to perform relevant optimization operations.

[0143] S412, RAN node device 1 executes relevant optimization operations specified by the AI ​​server.

[0144] In this step, if the relevant optimization operation involves one or more terminal devices, the RAN node device 1 sends an RRC reconfiguration message or an RRC release message to the terminal device connected to the base station, informing the terminal device to perform the relevant operation.

[0145] S413, RAN node device 1 notifies RAN node device 2 to perform relevant optimization operations through a RAN operation request message.

[0146] Among them, the optimization operation can be one or more operation indications and parameters required for the corresponding operations, such as terminal equipment switching indication, cell closing / opening indication, wireless resource activation / deactivation indication, power adjustment indication, RRM parameter reconfiguration indication, diversion operation indication, protocol layer parameter reconfiguration indication, etc.).

[0147] S414, RAN node device 2 executes relevant optimization operations in the RAN operation request message.

[0148] S415, the RAN node device sends an RRC reconfiguration message or an RRC release message to the UE connected to the RAN node device, informing the UE to perform related operations.

[0149] In this step, if the relevant optimization operation involves one or more terminal devices, the RAN node device 2 sends an RRC reconfiguration message or an RRC release message to the terminal device connected to the base station, informing the terminal device to perform the relevant operation.

[0150] From the above content, we can know that Figure 4 Network optimization methods and Figure 3 The network optimization methods in are basically the same, except that: the RAN node device on which the AI ​​server is deployed also needs to perform measurement configuration and perform measurement; when the base station on which the AI ​​server is deployed needs to perform RAN optimization operations, if the relevant optimization operations involve one or more terminal devices, the RAN node device where the AI ​​server is located can send an RRC reconfiguration message or an RRC release message to the terminal device connected to the RAN node to instruct the terminal device connected to the RAN node to perform the specified optimization operation.

[0151] In an embodiment of the present application, a base station deployed with an AI server can send an ML session establishment request and receive an ML session response message through an interface with another base station to request an adjacent base station to participate in the RAN optimization operation, without the need to establish an additional communication interface between the AI ​​server and the network side device, thereby saving network resources.

[0152] Figure 5 A schematic diagram of a process for establishing a communication interface between an AI server and a RAN node device according to an embodiment is shown. Figure 5 As shown, in one embodiment, the interface establishment process may include the following steps.

[0153] S501, when the AI ​​server is deployed outside the RAN node, the network management sends a configuration message or directly configures the address of the AI ​​server to the base station.

[0154] In some embodiments, if the AI ​​server is deployed inside the RAN node, step S501 does not need to be performed.

[0155] S502: The base station sends a communication interface establishment request according to the configured address of the AI ​​server.

[0156] In this step, if the interface between the AI ​​server and the RAN node is called an AI interface, the RAN node sends an AI interface establishment request message to the address of the AI ​​server to establish the AI ​​interface.

[0157] In one embodiment, the communication interface establishment request may include: measurements supported by the network side device (eg, base station); reporting methods of measurements supported by the network side device; and RAN optimization operations supported by the network side device.

[0158] In one embodiment, the communication interface establishment request may also include: a data plane channel address of a network side device.

[0159] S503, the AI ​​server sends an interface establishment response message to the base station to indicate whether the interface is successfully established.

[0160] In this step, if in S502, the communication interface establishment request received by the AI ​​server carries the data plane channel address of the network side device, the data plane channel address of the AI ​​server side may be carried in the interface establishment response message.

[0161] Through the above steps S501 to S503, a control plane interface of the AI ​​server for the RAN node can be established. The control plane interface can be used to transmit control messages and can also be used to transmit data required for machine learning, such as measurement data.

[0162] S504: Establish a data plane channel according to the data plane channel address configured by the AI ​​server and the data plane channel address on the base station side.

[0163] In the implementation of this application, the data required for machine learning can be transmitted between the network side device and the AI ​​server on the data plane channel. For example, some data with a large amount of data can be transmitted on the data plane channel, such as measurement data from the base station, to alleviate the data transmission pressure of the communication channel corresponding to the control plane interface and improve data transmission efficiency. The data plane channel established in this embodiment is not limited to transmitting data of a specified user.

[0164] Figure 6 A schematic diagram of a process for establishing a data channel between an AI server and a user device according to an embodiment is shown. Figure 6 As shown, in one embodiment, the interface establishment process may include the following steps.

[0165] S601, obtaining an A1 control plane interface established between an AI server and a RAN node device (eg, a base station).

[0166] The AI ​​server may be deployed outside the RAN node, or the AI ​​server may be deployed inside a RAN node.

[0167] S602: The AI ​​server or the base station where the AI ​​server is located sends a channel establishment request message to an adjacent base station.

[0168] As an example, the channel establishment request message may be, for example, a terminal device context establishment request message (UE AIContext Setup Request), and carry the data plane channel address and the terminal device identifier (UE ID) on the AI ​​server side.

[0169] S603: The base station sends a channel establishment response message to the AI ​​server or the base station where the AI ​​server is located.

[0170] As an example, the channel establishment response message may be, for example, a terminal equipment context establishment response message (UE AIContext Setup Response), and carry the data plane channel address on the base station side.

[0171] S604: Establish a data plane channel specified by the UEID and related to a specific user according to the data plane channel address configured by the AI ​​server and the data plane channel address on the base station side.

[0172] In this example, the RAN node and the AI ​​server can transmit the data required for ML related to a specific user on the data plane channel. Usually, some larger data volumes can be transmitted on the data plane channel, such as the measurement data of the user.

[0173] In an embodiment of the present application, the data required for machine learning can be transmitted between the RAN node device and the AI ​​server on the data plane channel. For example, some data with a large amount of data can be transmitted on the data plane channel, such as measurement data from the base station, to relieve the data transmission pressure of the communication channel corresponding to the control plane interface and improve data transmission efficiency. The data plane channel established in this embodiment is not limited to transmitting data of a specified user.

[0174] A server according to an embodiment of the present invention is described in detail below with reference to the accompanying drawings. Figure 7 FIG. 1 is a schematic diagram showing a structure of a server provided by an embodiment of the present invention. In one embodiment, the server may be a server with AI function, referred to as AI server, such as Figure 7 As shown, the server may include the following modules.

[0175] The measurement control information determination 710 is used to determine the network side measurement control information according to the pre-acquired policy information that the network needs to meet.

[0176] The measurement configuration request module 720 is used to send a session establishment request to a specified network side device to request the specified network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on the terminal device connected to the specified network side device.

[0177] The measurement report receiving module 730 receives the measurement report of the specified network side device and the measurement report of the terminal device.

[0178] The machine learning module 740 is used to perform machine learning for network optimization based on the measurement data and policy information in the received measurement report to obtain network optimization operation instructions. The network optimization operation instructions are used to instruct the specified network side equipment and terminal equipment to perform network optimization according to the network optimization operation instructions.

[0179] In one embodiment, the server also includes: a policy information acquisition module, used to obtain policy information that a pre-configured network needs to satisfy; or, in response to a received activation message, activate a machine learning function and obtain policy information that the network needs to satisfy carried in the activation message.

[0180] In one embodiment, the policy information includes object identification information and communication quality indicator information, and the communication quality indicator information is used to indicate the communication quality that the entity identified by the object identification information needs to achieve; in this embodiment, the measurement control information determination 710 can be specifically used to determine the network side device that needs to perform measurement according to the entity identified by the object identification information, as the designated network side device; and, according to the communication quality that the entity indicated by the communication quality indicator information needs to achieve, determine the measurement amount and measurement reporting method that the designated network side device needs to be configured as the network side measurement control information.

[0181] In one embodiment, the deployment location of the current server includes outside the network side device and inside the network side device; in this embodiment, the measurement configuration request module 720 can be specifically used to: if the deployment location of the current server is outside the network side device, send a session establishment request message to the specified network side device, and the session establishment request message includes network side measurement control information; if the deployment location of the current server is inside the network side device, perform measurement configuration on the network side device where the current server is located according to the network side measurement control information, and send a session establishment request message to the specified network side device, and the session establishment request message includes network side measurement control information.

[0182] In one embodiment, the server may further include: a session establishment response module, configured to determine, in response to a received session establishment response message, that measurement configuration of both the designated network side device and the terminal device is successful.

[0183] In one embodiment, the session establishment request, the session establishment response message and the received measurement report include a corresponding machine learning session identifier, and the machine learning session identifier is used to uniquely identify the machine learning process.

[0184] In one embodiment, the measurement report receiving module 730 may be specifically configured to receive a measurement report of a designated network side device and a measurement report of a terminal device sent by the designated network side device.

[0185] In one embodiment, the server may further include: a network operation request sending module, configured to send a network operation request message to a designated network side device, wherein the network operation request message includes a network optimization operation instruction and corresponding operation parameters.

[0186] In one embodiment, the current server communicates with a designated network side device through a predetermined interface, and the server also includes: a first predetermined interface determination module, which is used to establish a control plane interface between the current server and the designated network side device as a predetermined interface in response to a received control plane interface establishment request message if the current server is deployed outside the network side device; and a second predetermined interface determination module, which is used to obtain an existing communication transmission interface between the network side device where the current server is located and the designated network side device as a predetermined interface if the current server is deployed inside the network side device.

[0187] In one embodiment, the control plane interface establishment request message includes one or more of the following information items: measurements supported by the specified network side device, reporting methods supported by the specified network side device, network optimization operations supported by the specified network side device, and the data plane channel address of the specified network side device.

[0188] In one embodiment, the server also includes: a control plane interface establishment response sending module, which is used to send a control plane interface establishment response message to a specified network side device to indicate that the control plane interface is successfully established; if the control plane interface establishment request message includes the data plane channel address of the specified network side device, then when sending the control plane interface establishment response message to the specified network side device, the data plane channel address of the current server is carried in the control plane interface establishment response message.

[0189] According to the server of the embodiment of the present application, the measurement data of the wireless network side and the measurement data measured on the terminal side that are configured and received are used to perform machine learning model training to obtain network optimization operations, thereby performing in-depth analysis of the collected data through artificial intelligence and machine learning, and using intelligent network optimization methods to provide new optimization methods and network intelligent optimization processes for operator network optimization.

[0190] Figure 8 FIG. 2 is a schematic diagram showing the structure of a network side device provided by an embodiment of the present invention. Figure 8 As shown, the network side device may include the following modules.

[0191] The measurement configuration module 810 is used to perform measurement configuration according to the network side measurement control information in the session establishment request and perform measurement configuration on the terminal device connected to the specified network side device in response to receiving the session establishment request from the predetermined server;

[0192] The measurement report sending module 820 is used to send the measurement report of the current network side device and the measurement report of the received terminal device to a predetermined server. The measurement report of the current network side device and the measurement report of the terminal device are used in the predetermined server for machine learning for network optimization.

[0193] In one embodiment, the measurement configuration module 810 can be specifically used to: respond to a session establishment request, perform measurement configuration according to network side measurement control information, the network side measurement control information is used to indicate the measurement amount and measurement reporting method that the current network side device needs to configure; determine the measurement amount and measurement reporting method that the terminal device connected to the current network side device needs to configure according to the network side measurement control information, as the terminal side measurement control information; send a first wireless resource control message to the terminal device to instruct the terminal device to perform measurement configuration according to the terminal side measurement control information.

[0194] In one embodiment, the network side device may also include: a session establishment response message sending module, which is used to send a session establishment response message to a predetermined server if the current network side device measurement configuration is successful and a measurement configuration response message of the terminal device is received, so as to feedback to the predetermined server that the current network side device and the terminal device are both successfully measured and configured.

[0195] In one embodiment, the received session establishment request, session establishment response message, and measurement report sent to the predetermined server include a corresponding machine learning session identifier, and the machine learning session identifier is used to uniquely identify the machine learning process.

[0196] In one embodiment, the network side device may also include: an operation instruction receiving module, used to receive and execute network optimization operation instructions from a predetermined server; an operation instruction execution unit, used to determine the operations related to the terminal device in the network optimization operation instructions if the network optimization operation instructions involve the terminal device; and a related operation sending unit, used to send a second wireless resource control message to the terminal device to instruct the terminal device to perform related operations.

[0197] In one embodiment, the current network side device communicates with the predetermined server through a predetermined interface, and the network side device may also include: a predetermined interface establishment request module, which is used to send a control plane interface establishment request message to the predetermined server according to the pre-acquired address of the predetermined server if the deployment location of the predetermined server is outside the current network side device, so as to request the predetermined server to establish a control plane interface between the current network side device and the predetermined server as the predetermined interface; a communication transmission interface acquisition module, which is used to acquire the existing communication transmission interface between the current network side device and the network side device where the predetermined server is located as the predetermined interface if the deployment location of the predetermined server is inside the current network side device.

[0198] In one embodiment, the control plane interface establishment request message includes one or more of the following information items: measurements supported by the current network side device, reporting methods supported by the current network side device, network optimization operations supported by the current network side device, and the data plane channel address of the current network side device.

[0199] In one embodiment, the network side device may also include: a control plane interface establishment response receiving module, which is used to determine that the control plane interface between the current network side device and the predetermined server is successfully established in response to a received control plane interface establishment response message; wherein, if the control plane interface establishment request message includes the data plane channel address of the current network side device, then the received control plane interface establishment response message includes the data plane channel address of the predetermined server.

[0200] According to the network side device of the embodiment of the present application, under the control of the AI ​​server, measurement configuration can be performed on the network side device and the terminal device, and the measurement data obtained by the measurement performed by the network side device and the measurement data obtained by the measurement performed by the receiving terminal device can be sent to the AI ​​server for performing machine learning for network optimization on the AI ​​server, thereby receiving and executing the network optimization operation instructions obtained by machine learning to perform network optimization.

[0201] Fig. 9 FIG. 1 is a schematic diagram showing the structure of a network optimization system provided by an embodiment of the present invention. Fig. 9 As shown, the network optimization system may include a server 910 and one or more network-side devices 920 as follows.

[0202] Server 910, which can be used to execute the above embodiment in combination with Figure 1 Describes the network optimization method.

[0203] One or more network side devices 920, the network side device 920 is used to perform the above embodiment combined with Figure 2 Describes the network optimization method.

[0204] In this embodiment, the AI ​​server 910 is combined with Figure 7 The AI ​​server described in the embodiment has the same or equivalent structure and can execute the network optimization method applied to the AI ​​server described in the above embodiment; the network side device 920 is combined with Figure 8 The described network side device has the same or equivalent structure and can execute the network optimization method applied to the network side device described in the above embodiment.

[0205] It should be clear that the present invention is not limited to the specific configurations and processes described in the above embodiments and shown in the figures. For the convenience and brevity of description, a detailed description of the known methods is omitted here, and the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, which will not be repeated here.

[0206] Fig.10 is a block diagram illustrating an exemplary hardware architecture of a computing device capable of implementing an embodiment of the present invention.

[0207] like Fig.10 As shown, the computing device 1000 includes an input device 1001, an input interface 1002, a central processing unit 1003, a memory 1004, an output interface 1005, and an output device 1006. The input interface 1002, the central processing unit 1003, the memory 1004, and the output interface 1005 are connected to each other via a bus 1010, and the input device 1001 and the output device 1006 are connected to the bus 1010 via the input interface 1002 and the output interface 1005, respectively, and are further connected to other components of the computing device 1000.

[0208] Specifically, the input device 1001 receives input information from the outside and transmits the input information to the central processing unit 1003 through the input interface 1002; the central processing unit 1003 processes the input information based on the computer executable instructions stored in the memory 1004 to generate output information, temporarily or permanently stores the output information in the memory 1004, and then transmits the output information to the output device 1006 through the output interface 1005; the output device 1006 outputs the output information to the outside of the computing device 1000 for user use.

[0209] In one embodiment, Fig.10 The computing device shown can be implemented as a server, which may include: a memory configured to store a program; a processor configured to run the program stored in the memory to execute the network optimization method applied to the AI ​​server described in the above embodiment.

[0210] In one embodiment, Fig.10 The computing device shown can be implemented as a network side device, which may include: a memory configured to store programs; a processor configured to run the programs stored in the memory to execute the network optimization method applied to the network side device described in the above embodiment.

[0211] The above is only an exemplary embodiment of the present application and is not intended to limit the scope of protection of the present application. In general, various embodiments of the present application can be implemented in hardware or special circuits, software, logic or any combination thereof. For example, some aspects can be implemented in hardware, while other aspects can be implemented in firmware or software that can be executed by a controller, a microprocessor or other computing device, although the present application is not limited thereto.

[0212] Embodiments of the present application may be implemented by executing computer program instructions by a data processor of a mobile device, for example in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0213] The block diagram of any logic flow in the accompanying drawings of the present application can represent program steps, or can represent interconnected logic circuits, modules and functions, or can represent a combination of program steps and logic circuits, modules and functions. The computer program can be stored in a memory. The memory can have any type suitable for the local technical environment and can be implemented using any suitable data storage technology, such as but not limited to read-only memory (ROM), random access memory (RAM), optical memory device and system (digital versatile disc DVD or CD disc), etc. Computer-readable media may include non-transient storage media. The data processor can be any type suitable for the local technical environment, such as but not limited to a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (FGPA) and a processor based on a multi-core processor architecture.

[0214] By way of exemplary and non-limiting examples, a detailed description of exemplary embodiments of the present application has been provided above. However, various modifications and adjustments to the above embodiments will be apparent to those skilled in the art when considered in conjunction with the accompanying drawings and claims, but will not depart from the scope of the present invention. Therefore, the proper scope of the present invention will be determined according to the claims.

Claims

1. A network optimization method, characterized in that: The method comprises: Determine network-side measurement control information according to pre-acquired policy information that the network needs to meet; Sending a session establishment request to a specified network side device to request the specified network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on a terminal device connected to the specified network side device; Receiving a measurement report of the designated network side device and a measurement report of the terminal device; Based on the measurement data in the received measurement report and the policy information, machine learning for network optimization is performed to obtain a network optimization operation instruction, wherein the network optimization operation instruction is used to instruct the designated network-side device and the terminal device to perform network optimization according to the network optimization operation instruction; The policy information includes object identification information and communication quality indicator information, where the communication quality indicator information is used to indicate the communication quality required to be achieved by the entity identified by the object identification information; and determining the network-side measurement control information according to the pre-acquired policy information that the network needs to meet, including: Determining, according to the entity identified by the object identification information, a network side device that needs to perform measurement as a designated network side device; and Determine, according to the communication quality required to be achieved by the entity indicated by the communication quality indicator information, a measurement amount and a measurement reporting method required to be configured for the designated network side device as the network side measurement control information; The server is deployed at a location outside the network side device or inside the network side device, wherein the server is deployed at a location outside the network side device, which means that the server is deployed neither inside the network side device nor in the core network; wherein the network side device includes a wireless access network RAN ​​node, and the RAN node includes a base station.

2. The method according to claim 1, characterized in that Before determining the network-side measurement control information according to the pre-acquired policy information that the network needs to satisfy, the method further includes: Obtaining policy information that a pre-configured network needs to satisfy; or, In response to the received activation message, the machine learning function is activated, and the policy information that needs to be satisfied by the network carried in the activation message is obtained.

3. The method according to claim 1, characterized in that: The deployment location of the current server includes outside the network side device and inside the network side device; sending the session establishment request to the specified network side device includes: If the deployment location of the current server is outside the network side device, sending the session establishment request message to the specified network side device, wherein the session establishment request message includes the network side measurement control information; If the current server is deployed inside the network side device, the network side device where the current server is located is measured and configured according to the network side measurement control information, and the session establishment request message is sent to the specified network side device, and the session establishment request message includes the network side measurement control information.

4. The method according to claim 1, characterized in that After sending the session establishment request to the specified network side device, the method further includes: In response to the received session establishment response message, it is determined that both the designated network side device and the terminal device have successfully measured and configured.

5. The method according to claim 4, characterized in that The session establishment request, the session establishment response message and the received measurement report include a corresponding machine learning session identifier, and the machine learning session identifier is used to uniquely identify a machine learning process.

6. The method according to claim 1, characterized in that The receiving the measurement report of the designated network side device and the measurement report of the terminal device includes: Receive the measurement report of the designated network side device and the measurement report of the terminal device sent by the designated network side device.

7. The method according to claim 1, characterized in that After performing machine learning for network optimization based on the measurement data in the received measurement report and the policy information to obtain a network optimization operation instruction, the method further includes: Sending a network operation request message to the specified network side device, wherein the network operation request message includes the network optimization operation instruction and corresponding operation parameters.

8. The method according to claim 1, characterized in that: The current server communicates with the specified network side device through a predetermined interface. Before sending the session establishment request to the specified network side device, the method further includes: If the deployment location of the current server is outside the network side device, in response to the received control plane interface establishment request message, establish a control plane interface between the current server and the specified network side device as the predetermined interface; If the deployment location of the current server is inside the network side device, then the existing communication transmission interface between the network side device where the current server is located and the specified network side device is obtained as the predetermined interface.

9. The method according to claim 8, characterized in that The control plane interface establishment request message includes one or more of the following information items: measurements supported by the specified network side device, reporting methods supported by the specified network side device, network optimization operations supported by the specified network side device, and the data plane channel address of the specified network side device.

10. The method according to claim 9, characterized in that After establishing the control plane interface between the current server and the specified network side device as the predetermined interface in response to the received control plane interface establishment request message, the method further includes: Sending a control plane interface establishment response message to the specified network side device to indicate that the control plane interface is successfully established; If the control plane interface establishment request message includes the data plane channel address of the specified network side device, when sending a control plane interface establishment response message to the specified network side device, the data plane channel address of the current server is carried in the control plane interface establishment response message.

11. A network optimization method, characterized in that: The method comprises: In response to receiving a session establishment request from a predetermined server, performing measurement configuration according to the network side measurement control information in the session establishment request and performing measurement configuration on a terminal device connected to a specified network side device; Sending the measured measurement report of the current network side device and the received measurement report of the terminal device to the predetermined server, where the measurement report of the current network side device and the measurement report of the terminal device are used to perform machine learning for network optimization in the predetermined server; The network-side measurement control information is determined by the predetermined server according to policy information, the policy information includes object identity information and communication quality indicator information, and the communication quality indicator is used to indicate the communication quality that the entity identified by the object identity information needs to achieve; The entity identified by the object identity information is used to indicate the network side device, and the network side measurement control information is used to indicate the measurement amount and measurement reporting method that the current network side device needs to configure; The deployment location of the predetermined server is outside the network side device or inside the network side device, wherein the deployment location of the predetermined server is outside the network side device, which means that the deployment location of the predetermined server is neither inside the network side device nor in the core network.

12. The method according to claim 11, characterized in that The step of performing measurement configuration according to the network side measurement control information in the session establishment request and performing measurement configuration on the terminal device connected to the designated network side device in response to receiving the session establishment request from the predetermined server includes: In response to the session establishment request, performing measurement configuration according to the network side measurement control information; According to the network-side measurement control information, determine the measurement quantity and measurement reporting mode that the terminal device connected to the current network-side device needs to be configured as the terminal-side measurement control information; A first wireless resource control message is sent to the terminal device to instruct the terminal device to perform measurement configuration according to the terminal side measurement control information.

13. The method according to claim 11, characterized in that If the measurement configuration of the current network side device is successful and a measurement configuration response message of the terminal device is received, a session establishment response message is sent to the predetermined server to feedback to the predetermined server that the measurement configuration of both the current network side device and the terminal device is successful.

14. The method according to claim 13, characterized in that The received session establishment request, the session establishment response message, and the measurement report sent to the predetermined server include a corresponding machine learning session identifier, and the machine learning session identifier is used to uniquely identify the machine learning process.

15. The method according to claim 11, characterized in that The method further comprises: Receiving and executing the network optimization operation instruction from the predetermined server; If the network optimization operation instruction involves the terminal device, determining the operation in the network optimization operation instruction related to the terminal device; Send a second wireless resource control message to the terminal device to instruct the terminal device to perform the related operation.

16. The method according to claim 11, characterized in that The current network side device communicates with the predetermined server through a predetermined interface. In response to receiving a session establishment request from the predetermined server, before performing measurement configuration according to the network side measurement control information in the session establishment request and performing measurement configuration on the terminal device connected to the specified network side device, the method further includes: If the deployment location of the predetermined server is outside the current network side device, sending a control plane interface establishment request message to the predetermined server according to the pre-acquired address of the predetermined server to request the predetermined server to establish a control plane interface between the current network side device and the predetermined server as the predetermined interface; If the deployment location of the predetermined server is inside the current network side device, then an existing communication transmission interface between the current network side device and the network side device where the predetermined server is located is obtained as the predetermined interface.

17. The method according to claim 16, characterized in that The control plane interface establishment request message includes one or more of the following information items: measurements supported by the current network side device, reporting methods supported by the current network side device, network optimization operations supported by the current network side device, and the data plane channel address of the current network side device.

18. The method according to claim 17, characterized in that Also includes: In response to the received control plane interface establishment response message, it is determined that the control plane interface between the current network side device and the predetermined server is successfully established; wherein, If the control plane interface establishment request message includes the data plane channel address of the current network side device, the received control plane interface establishment response message includes the data plane channel address of the predetermined server.

19. A server, characterized in that: include: A measurement control information determination module, used to determine network-side measurement control information according to pre-acquired policy information that the network needs to meet; A measurement configuration request module, used to send a session establishment request to a specified network side device to request the specified network side device to perform measurement configuration according to the network side measurement control information and to perform measurement configuration on a terminal device connected to the specified network side device; A measurement report receiving module, used to receive the measurement report of the specified network side device and the measurement report of the terminal device; A machine learning module, configured to perform machine learning for network optimization based on the measurement data in the received measurement report and the policy information, and obtain a network optimization operation instruction, wherein the network optimization operation instruction is used to instruct the designated network side device and the terminal device to perform network optimization according to the network optimization operation instruction; The policy information includes object identification information and communication quality indicator information, wherein the communication quality indicator information is used to indicate the communication quality required to be achieved by the entity identified by the object identification information; The measurement control information determination module is specifically used to: determine, according to the entity identified by the object identification information, a network side device that needs to perform measurement as the designated network side device; and, according to the communication quality required to be achieved by the entity indicated by the communication quality indicator information, determine the measurement amount and measurement reporting method that need to be configured for the designated network side device as the network side measurement control information; The server is deployed at a location outside the network side device or inside the network side device, wherein the server is deployed at a location outside the network side device, which means that the server is deployed neither inside the network side device nor in the core network; wherein the network side device includes a wireless access network RAN ​​node, and the RAN node includes a base station.

20. A network side device, characterized in that: include: A measurement configuration module, configured to, in response to receiving a session establishment request from a predetermined server, perform measurement configuration according to the network side measurement control information in the session establishment request and perform measurement configuration on a terminal device connected to a specified network side device; A measurement report sending module, used to send the measurement report of the current network side device and the received measurement report of the terminal device to the predetermined server, wherein the measurement report of the current network side device and the measurement report of the terminal device are used in the predetermined server to perform machine learning for network optimization; The network-side measurement control information is determined by the predetermined server according to policy information, the policy information includes object identity information and communication quality indicator information, and the communication quality indicator is used to indicate the communication quality that the entity identified by the object identity information needs to achieve; The entity identified by the object identity information is used to indicate the network side device, and the network side measurement control information is used to indicate the measurement amount and measurement reporting method that the current network side device needs to configure; The deployment location of the predetermined server is outside the network side device or inside the network side device, wherein the deployment location of the predetermined server is outside the network side device, which means that the deployment location of the predetermined server is neither inside the network side device nor in the core network.

21. A server, comprising: one or more first processors; A memory having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the network optimization method described in any one of claims 1-10.

22. A network side device, comprising: one or more second processors; A memory having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the network optimization method described in any one of claims 11-18.

23. A network optimization system, comprising: A server, wherein the server is used to execute the network optimization method according to any one of claims 1 to 10; One or more network-side devices, wherein the network-side devices are used to execute the network optimization method described in any one of claims 11-18.

24. A storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the network optimization method according to any one of claims 1 to 10 or any one of claims 11 to 18 is implemented.

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