CN114599056A - Mobile communication system control method, network controller, system and storage medium - Google Patents
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Abstract
The embodiment of the application provides a mobile communication system control method, a network controller, a system and a storage medium, wherein the method comprises the following steps: sending the knowledge graph spectrum stored in the knowledge agent to a system simulation engine in the twin mobile communication system so that the system simulation engine can configure the twin mobile communication system according to the knowledge graph, wherein the twin mobile communication system is a simulation system of the mobile communication system; receiving a control strategy generated by the knowledge agent and issuing the control strategy to a system simulation engine so that the system simulation engine can drive the twin mobile communication system to simulate according to the control strategy and feed back a network performance knowledge map to the knowledge agent after the simulation is finished, wherein the network performance knowledge map is used for enabling the knowledge agent to generate an optimized control strategy; and receiving the optimized management and control strategy sent by the knowledge agent, and controlling the mobile communication system to execute corresponding management and control actions according to the optimized management and control strategy.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method, a network controller, a system, and a storage medium for managing and controlling a mobile communication system.
Background
The mobile communication system includes many devices, so there is a certain control difficulty. At present, a mobile communication system adopts a manually defined management and control strategy for management and control, the method not only depends on management experience of management personnel, but also has the problems of large difficulty in verification of management and control effect, long management and control adjustment period and the like after the management and control strategy is applied to the mobile communication system, so that the management and control method of the current mobile communication system has certain limitation.
Disclosure of Invention
Based on this, embodiments of the present application provide a method, a network controller, a system, and a storage medium for managing and controlling a mobile communication system, so as to solve the limitations of the management and control method of the mobile communication system in the prior art.
In a first aspect, an embodiment of the present application provides a method for managing and controlling a mobile communication system, including:
sending a knowledge graph spectrum stored in a knowledge agent to a system simulation engine in a twin mobile communication system to enable the system simulation engine to configure the twin mobile communication system according to the knowledge graph, wherein the twin mobile communication system is a simulation system of the mobile communication system;
receiving a control strategy generated by the knowledge agent and issuing the control strategy to the system simulation engine so that the system simulation engine can drive the twin mobile communication system to simulate according to the control strategy and feed back a network performance knowledge graph to the knowledge agent after the simulation is finished, wherein the network performance knowledge graph is used for enabling the knowledge agent to generate an optimized control strategy;
and receiving the optimized management and control strategy sent by the knowledge agent, and controlling the mobile communication system to execute corresponding management and control actions according to the optimized management and control strategy.
In a second aspect, an embodiment of the present application provides a network management controller, including a processor and a memory; the memory for storing a computer program; the processor is configured to execute the computer program and implement the mobile communication system management and control method according to the first aspect when executing the computer program.
In a third aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program causes the processor to implement the mobile communication system management and control method according to the first aspect.
In a fourth aspect, an embodiment of the present application provides a management and control system, including the network management controller, the knowledge agent, the mobile communication system, and the twin mobile communication system according to the second aspect.
The embodiment of the application provides a mobile communication system control method, a network controller, a system and a storage medium, wherein the method comprises the following steps: sending the knowledge graph spectrum stored in the knowledge agent to a system simulation engine in the twin mobile communication system so that the system simulation engine can configure the twin mobile communication system according to the knowledge graph, wherein the twin mobile communication system is a simulation system of the mobile communication system; receiving a control strategy generated by the knowledge agent and issuing the control strategy to a system simulation engine so that the system simulation engine can drive the twin mobile communication system to simulate according to the control strategy and feed back a network performance knowledge map to the knowledge agent after the simulation is finished, wherein the network performance knowledge map is used for enabling the knowledge agent to generate an optimized control strategy; and receiving the optimized management and control strategy sent by the knowledge agent, and controlling the mobile communication system to execute corresponding management and control actions according to the optimized management and control strategy. It can be understood that the twin mobile communication system is a simulation system of the mobile communication system, and the twin mobile communication system is a digital system, so that the verification difficulty of the management and control effect can be effectively reduced through the twin mobile communication system, the management and control adjustment period is effectively shortened, and the limitation of the management and control mode of the mobile communication system in the prior art is solved.
Drawings
FIG. 1 is a schematic block diagram of a management system provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of a method for managing and controlling a mobile communication system according to an embodiment of the present application;
fig. 3 is an alternative system configuration diagram of a mobile communication system in the embodiment of the present application;
FIG. 4 is an alternative system block diagram of a twin mobile communications system in an embodiment of the present application;
FIG. 5 is a schematic flow chart illustrating the simulation of a twin mobile communication system driven by a system simulation engine according to an embodiment of the present application;
fig. 6 is another schematic flow chart illustrating a management and control method of a mobile communication system according to an embodiment of the present application;
fig. 7 is a schematic block diagram of a structure of a network management controller according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort belong to the protection scope of the present specification.
The flow diagrams depicted in the figures are merely illustrative and do not necessarily include all of the elements and operations/steps, nor do they necessarily have to be performed in the order depicted. For example, some operations/steps may be decomposed, combined or partially combined, so that the actual execution order may be changed according to the actual situation.
Some embodiments of the present description will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
The embodiment of the present application may be applied to a management and control system, as shown in fig. 1, the management and control system may include a network controller, a knowledge agent, a mobile communication system, and a twin mobile communication system, where the method for managing and controlling a mobile communication system according to the embodiment of the present application may be applied to the network controller, that is, the network controller may execute the method according to the embodiment of the present application to manage and control the mobile communication system.
Based on this, the method for managing and controlling a mobile communication system provided in the embodiment of the present application may be applied to a network manager, as shown in fig. 2, the method may include, but is not limited to, steps S10 to S30.
And step S10, sending the knowledge graph spectrum stored in the knowledge agent to a system simulation engine in the twin mobile communication system, so that the system simulation engine can configure the twin mobile communication system according to the knowledge graph, wherein the twin mobile communication system is a simulation system of the mobile communication system.
In some embodiments, as shown in fig. 3, the mobile communication system may include a user terminal, an air interface, an access network, a bearer network, a core network, an application server, a storage system, a computing system, and the like, where the user terminal may include a mobile phone, a CPE (Customer Premise Equipment), a laptop, and the like; the air interface refers to an air interface between the user terminal and the access network, and may include an indoor WiFi wireless channel, an outdoor wireless channel, a satellite communication channel, and the like; the access network may include 2/3/4/5G Terrestrial cellular mobile network or NTN (Non-Terrestrial network) satellite communication network, for example, including macro base station, micro base station, pico base station, femto base station, and femto base station; the bearer Network may include a PTN (Packet Transport Network), an OTN (Optical Transport Network), and the like, for example, an Optical fiber Network, a Wireless Mesh return Network (Wireless Mesh Network), and the like; the core network may include 2/3/4/5G core network, etc.; the application server refers to a server for deploying application services, is used for processing opposite-end services, and can comprise a website server, a video on demand server and the like; the storage system is used for storing the operation and maintenance data of the mobile communication system; the computing system is used to provide administrative computing functionality for the mobile communications system and may include, for example, an edge computing device.
In some embodiments, the intellectual agent may be configured to generate a knowledge graph according to operation and maintenance data stored in a storage system in the mobile communication system, that is, the knowledge graph stored in the intellectual agent is generated according to the operation and maintenance data of the mobile communication system, where the operation and maintenance data may include work parameter information, drive test data, MR Report (Measurement Report), log file, 3D map, KPI (Key Performance Indicator) statistics, intelligent edge cache data, and the like, where the work parameter information may include an antenna downtilt of a base station, a GPS location of the base station, and the like; MR reports may include user terminal measurement reports, etc.; the intelligent edge cache data refers to application data stored in network element equipment close to the user terminal. The embodiment of the present application is not limited to the manner in which the knowledgeable agent generates the knowledgeable graph according to the operation and maintenance data, and for example, the knowledgeable graph may be generated by using an objective data modeling method, or may be generated based on a deep learning AI model.
Based on the limitation, the inventor finds that the limitation can be solved by a Digital Twin (Digital Twin) technology, wherein the Digital Twin technology is a simulation process integrating multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities by fully utilizing data such as physical models, sensor updates and operation histories, and mainly constructs a same entity in a Digital world by digitally simulating events (objects) in the physical world, so that the process of understanding, analyzing and optimizing the physical entities is realized. Based on the idea, the knowledge graph spectrum stored in the knowledge agent can be sent to the system simulation engine in the twin mobile communication system, so that the system simulation engine can configure the twin mobile communication system according to the knowledge graph, and therefore, the configured twin mobile communication system is the simulation system of the mobile communication system.
In some embodiments, the knowledge-graph includes a radio environment knowledge-graph, a radio network element knowledge-graph, a network management knowledge-graph, and a user terminal knowledge-graph.
The wireless environment knowledge graph may include geographic Information features, wireless channel features, coverage features, and the like, for example, the geographic Information features may include a Cell ID (which may be understood as a Cell number), a Cell longitude and latitude, a terminal longitude and latitude, a Point of Information (POI) partition Information, grid Information, and the like, where the Cell ID may include ID Information and the like composed of an MCC (Mobile Country Code), an MNC (Mobile Network Code, Mobile Network number), and a CI (Cell Identity), the POI partition Information may include a POI number, a POI type, a POI area proportion, and the like, and the grid Information may include a grid ID, a grid longitude and latitude, and the like; the wireless channel characteristics may include beam pairing characteristics, a channel LOS (Line of Sight) attribute, a channel multipath fading characteristic, a channel DOA (Direction of arrival) distribution characteristic, an uplink and downlink RI (Rank Indicator) distribution, an uplink and downlink PHR (Power Headroom Report) distribution, a User channel PMI (Precoding Matrix Indicator) weight, a cell Interference characteristic, and the like, where the beam pairing characteristics may include MU-MIMO (Multi-User Multi-Input Multi-Output) pairing success probability, and the like, and the cell Interference characteristic may include an uplink RB (Resource Block) average NI (Noise Interference, Noise indication), an Interference slot (slot) level fluctuation state, and the like; the coverage characteristics may include a Reference Signal Receiving Power (RSRP), a serving neighbor RSRP, a Modulation and Coding Scheme (MCS), a Block Error Rate (BLER), a Channel Quality Indicator (CQI), and a Block Error Rate (BLER).
The Radio network Element knowledge graph may include a Control plane feature, a user plane feature, and the like, for example, the Control plane feature may include a load feature, a Resource usage feature, an energy consumption feature, a KPI feature, an event feature, and the like, where the load feature may include an RRC (Radio Resource Control) online average user number, a PDCP (Packet Data Convergence Protocol) layer Data traffic, an MAC layer Data traffic, load smoothness, and the like, the Resource usage feature may include an uplink and downlink PRB (Physical Resource Block) utilization rate, an uplink and downlink CCE (Control Channel Element) scheduling number, a Control plane CPU utilization rate, a baseband processing board Resource utilization rate, and the like, the energy consumption feature may include an idle symbol occupation ratio, a symbol turn-off occupation ratio, a slot turn-off occupation ratio, a Channel turn-off occupation ratio, and the like, the KPI characteristics can include RRC connection establishment success rate, wireless disconnection rate, switching success rate and the like, and the event characteristics can include channel turn-off event record, switching success/failure record, equipment state abnormity, system alarm information and the like; the user plane features may include service distribution features, service awareness features, service traffic features, and the like, where the service distribution features may include packet service occupancy, VoNR (Voice over New Radio, which is a call solution based on pure 5G access and realizes that both Voice service and data service are carried in a 5G network) user number, game-like service occupancy, WeChat service occupancy, NGBR (Non Guaranteed Rate) service occupancy, PDCP (packet data Rate) layer delay, RLC layer delay, and the like, the service awareness features refer to subjective feelings of a user on quality and performance of a specific application service, may include cell quality difference user distribution ratio, real-time game awareness, WeChat awareness, VoNR awareness, 5QI2 video awareness, NGBR service awareness, and the like, the service traffic features may include UE service Rate distribution, UE second-level cumulative BSR (Buffer Status Report, buffer status report), UE cumulative scheduling TbSize (transport block size), and user plane throughput, etc.
The network management knowledge graph may include network configuration, algorithm strategy, networking structure, and the like, and for example, the network configuration may include slice resource configuration, base station operating Frequency points, base station transmitting power, base station antenna downtilt, base station antenna number, and base station FDD (Frequency Division Duplex)/TDD (Time Division Duplex) systems; the algorithm strategy can comprise a network slice control algorithm, an MAC (media access control) layer scheduling algorithm, a PDCP (packet data convergence protocol) layer data distribution algorithm, an MU-MIMO (multiple user multiple input multiple output) pairing algorithm and the like; the networking structure may include an access network structure, a bearer network structure, a core network structure, and the like, where the access network structure may include the number, type, and the like of base stations, the bearer network structure may include backhaul Mesh networking, and the core network structure may include an SA networking (Stand Alone networking), an NSA networking (Non-Stand Alone networking), and the like.
The user terminal knowledge graph may include behavior features, service features, perception features, and the like, for example, the behavior features may include state features, movement behavior features, action features of VR (Virtual Reality)/AR (Augmented Reality) applications, and the like, where the movement behavior features may include a terminal motion trajectory; the service features may include application layer semantic features and service category features, etc., wherein the application layer semantic features may include natural language, visual semantics, image semantics, etc., and the service category features may include packets, VoNR, etc.; the perception features refer to subjective feelings of the user, and may include video QoE (Quality of Experience) perception features, visual perception features, auditory perception features, tactile perception features, olfactory perception features, gustatory perception features, and the like.
In some embodiments, as shown in fig. 4, the twin mobile communication system includes a plurality of twin communication devices, a twin air interface, a terminal motion model (not shown), and a service model (not shown), where the twin air interface includes a channel model and an antenna model. Based on this, the aforementioned "system simulation engine configures the twin mobile communication system according to the knowledge graph", may include, but is not limited to, the following: the method comprises the steps of configuring software algorithm parameters of a plurality of twin communication devices according to a wireless network element knowledge graph, configuring hardware parameters and software algorithm strategies of the plurality of twin communication devices according to a network management knowledge graph, configuring a channel model according to a wireless environment knowledge graph, configuring an antenna model according to the network management knowledge graph and configuring a terminal motion model and a service model according to a user terminal knowledge graph.
From the foregoing, it can be seen that a mobile communication system includes a plurality of communication devices (these communication devices are referred to as actual devices for convenience of description), and since a twin mobile communication system is a corresponding simulation system, the twin mobile communication system includes twin communication devices corresponding to these actual devices. The twin communication device may include an actual communication device (i.e. an actual product), or may include a virtual device simulated by software, for example, a virtual device simulated by oai (openair interface) software, and thus, the twin communication device may include a twin user terminal, a twin access network, a twin bearer network, a twin core network, a twin internet, a twin application server, a twin storage system, a twin computing system, and the like. For example, the twin user terminal may be a virtual device simulated by OAI software, and is used to simulate a user terminal in an actual mobile communication system, and the twin user terminal has all communication functions specified by a 3GPP (3rd Generation Partnership Project) Protocol, for example, RRC (Radio Resource Control), PDCP (Packet Data Convergence Protocol), RLC (Radio Link Control, Radio Link Layer Control Protocol), MAC (Media Access Control), PHY (Physical Layer, port Physical Layer), S1 interface, X2 interface, and application Layer. Illustratively, the twin access Network may include a twin base station, which may be a virtual device simulated by OAI software and used for simulating a base station in an actual mobile communication system, and the twin base station has all communication functions specified by a 3GPP protocol, such as NAS (Network Attached Storage), RRC, PDCP, RLC, MAC, and PHY. Illustratively, the twin carrier web may be an optical fiber or a mesh wire, or the like. For example, the twin core network may be a virtual device simulated by OAI software, and is used to simulate a core network in an actual mobile communication system, and the twin core network has all communication functions specified by a 3GPP protocol, such as an HSS (Home Subscriber Server), an MME (Mobility Management Entity), an SGW (Serving GateWay), and a PGW (Packet data GateWay). For example, the twin internet, the twin application server, the twin storage system, and the twin computing system may be virtual devices processed by software simulation, or may be simulated by a system simulation engine or the like to simulate corresponding functions.
Therefore, the system simulation engine can configure the software algorithm parameters of each twin communication device according to the wireless network element knowledge graph, and configure the hardware parameters and the software algorithm strategy of each twin communication device according to the network management knowledge graph. Exemplarily, the system simulation engine may configure a UE (User Equipment) capability, a physical layer algorithm parameter, an MAC layer algorithm parameter, a UE reported neighbor relation, a UE uplink and downlink MCS (Modulation and Coding Scheme), and the like of the twin User terminal according to the wireless network element knowledge graph and the network management knowledge graph; illustratively, the system simulation engine may configure the base station ID, the geographical information, the physical layer algorithm parameter, the MAC layer algorithm parameter, the KPI performance, etc. of the twin base station (one of the twin access networks) according to the wireless network element knowledge map and the network management knowledge map.
In addition, the system simulation engine may further configure a channel model according to the wireless environment knowledge graph, where the channel model may include a path loss parameter, a channel characteristic parameter, an interference characteristic parameter, and the like. Illustratively, the system simulation engine may configure the path loss parameter according to a user service cell RSRP, a user service neighbor cell RSRP, and downlink reference signal power in the radio environment knowledge graph, a specific configuration manner may be a data fitting method, data fitting may be divided into two manners, i.e., a single time slice manner and a continuous time slice manner, and when the data is a single time slice manner, that is, only one set of data is present, the path loss parameter is determined according to the following formula.
PLi，j＝dlrstxpoweri-PSRPi，j
Wherein PLi,jIndicating a path loss parameter, dlrstxpower, between the user terminal j and the cell iiIndicating the reference signal transmit power, PSRP, of cell ii,jRepresenting the RSRP of the cell i reported by the terminal j; when the data is a continuous time slice, that is, there are multiple groups of data, a plurality of path loss samples are respectively calculated according to the formula, then curve fitting is performed on the path loss samples to obtain corresponding probability distribution, and finally a random number is generated according to the probability distribution, wherein the random number is a path loss parameter. Of course, the path loss parameter may also be configured by a ray tracing algorithm, and the specific process is not limited in the embodiment of the present application. Illustratively, the channel characteristic parameters may include beam pairing characteristics, channel LOS attributes, channel multipath fading characteristics, channel DOA distribution characteristics, uplink and downlink RI distributions, uplink and downlink PHR distributions, user channel PMI weights, and the like, and the system simulation engine may be configured according to the radio channel characteristics in the radio environment knowledge graph. For example, the interference characteristic parameters may include an uplink RB average NI and an interference slot level fluctuation state, and the system simulation engine may perform the interference estimation according to the cell interference in the radio environment knowledge graphAnd (5) feature configuration.
In addition, the system simulation engine may further configure an antenna model according to the network management knowledge graph, where the antenna model is used to simulate antenna gains in the horizontal direction and the vertical direction of the base station antenna 360 degrees in the mobile communication system, and the system simulation engine may configure according to the network management knowledge graph, for example, according to knowledge data about drive test data in the network management knowledge graph.
In addition, the system simulation engine may further configure a terminal motion model and a service model according to the user terminal knowledge graph, where the terminal motion model is used to simulate the position of the user terminal in the mobile communication system. In addition, the service model may include load characteristic parameters, service characteristic parameters, and the like, for example, the load characteristic parameters may include uplink and downlink PRB utilization, RRC online average user number, uplink and downlink CCE utilization, and the service characteristic parameters may include BSR, service type, service packet size, service packet number, service packet interaction flow, service packet interval time, and the like.
In some embodiments, the twin mobile communication system further comprises an environmental similarity contrast module for: after the system simulation engine configures the twin mobile communication system, determining the reduction degree of the twin mobile communication system to the mobile communication system according to the same communication characteristics of the mobile communication system and the twin mobile communication system, and updating the twin mobile communication system according to the knowledge graph when the reduction degree is detected to be lower than a preset threshold value.
As can be seen from the foregoing, the twin mobile communication system and the mobile communication system are substantially identical in entity attributes, states, behaviors and wireless environment, and therefore in order to maintain this state, the degree of reduction of the mobile communication system by the twin mobile communication system may be monitored, and the twin mobile communication system may be updated (i.e., reconfigured) according to the knowledge map upon detection of the degree of reduction being below a preset threshold to ensure that the twin mobile communication system is able to remain identical in all respects to the actual mobile communication system. In some embodiments, the system simulation engine may determine the degree of restitution based on one or more communication characteristics that are the same for both systems, where the communication characteristics may include any of the characteristics described above, and the degree of restitution may be determined according to the following formula.
Where S represents the degree of reduction, abs () represents the absolute value, TrealAnd TtwinRespectively representing the same communication characteristics of the actual mobile communication system and the twin mobile communication system, and in addition, the preset threshold value can be reasonably set according to actual requirements.
And step S20, receiving the control strategy generated by the knowledge agent and issuing the control strategy to the system simulation engine, so that the system simulation engine can drive the twin mobile communication system to simulate according to the control strategy and feed back a network performance knowledge graph to the knowledge agent after the simulation is finished, wherein the network performance knowledge graph is used for enabling the knowledge agent to generate the optimized control strategy.
And step S30, receiving the optimized management and control strategy sent by the knowledge agent, and controlling the mobile communication system to execute corresponding management and control actions according to the optimized management and control strategy.
The management and control policy mainly adjusts a working state and/or a working flow of the communication device, and is mainly applied to an access network and a core network, and exemplarily, the management and control policy may include adjusting algorithm parameters, a flow or a type of a physical layer, an MAC layer, an RLC layer, a PDCP layer, an RRC layer, a TCP layer, or an IP layer of the base station, and the management and control policy may further include adjusting a hardware operation flow, a handover flow, or a paging flow of the device. The network performance knowledge graph may be used to represent a control effect of a control policy, and may include PDCP layer data traffic, MAC layer data traffic, uplink and downlink PRB utilization, uplink and downlink CCE scheduling times, user SINR (Signal to Interference plus Noise Ratio), user MCS, user BLER, RRC connection establishment success rate, radio drop rate, handover success rate, or user service awareness MOS (Mean Opinion Score) Score.
The twin mobile communication system after configuration is a simulation system of the mobile communication system, and the two are basically consistent in entity attribute, state, behavior and wireless environment, so that the control strategy is issued to the system simulation engine, and the system simulation engine drives the twin mobile communication system to perform simulation according to the control strategy, which is equivalent to the situation that a network controller controls the mobile communication system to execute corresponding control action according to the control strategy, and the twin mobile communication system is a virtual digital system, so that the network performance knowledge graph can be generated after the simulation of the twin mobile communication system is finished, and the network performance knowledge graph corresponding to the control strategy can be rapidly acquired. Therefore, the management and control effect of the management and control strategy can be known through the network performance knowledge graph, namely, the network performance of the system becomes better or worse after the management and control strategy is applied, so that the knowledge agent can generate the optimized management and control strategy and send the optimized management and control strategy to the network management and control body, therefore, the network management and control body can control the mobile communication system to execute corresponding management and control actions according to the optimized management and control strategy, wherein the optimized management and control strategy is the management and control strategy with the standard or optimal management and control effect. It can be understood that the verification difficulty of the management and control effect can be effectively reduced through the twin mobile communication system, so that the management and control adjustment period is effectively shortened, and the limitation of the management and control mode of the mobile communication system in the prior art is solved.
In some embodiments, a management and control policy may be issued to the system simulation engine, so that the system simulation engine drives the twin mobile communication system to perform simulation according to the management and control policy and sends the network performance knowledge graph to the knowledgebase after the simulation is completed, so that the knowledgebase may obtain a management and control effect of the management and control policy according to the network performance knowledge graph, for example, obtain the management and control effect according to a user SINR value, and if the user SINR value does not reach a standard (for example, does not reach a certain threshold), the knowledgebase may optimize to generate an optimized management and control policy and send the optimized management and control policy to the network manager, so that the network manager may control the mobile communication system to perform a corresponding management and control action according to the optimized management and control policy. It can be understood that the optimized management and control policy is a management and control policy whose management and control effect meets the standard, that is, after the policy is applied to the mobile communication system, the network performance of the system can meet the standard, for example, the SINR value of the user can reach the threshold.
In some embodiments, the multiple control policies may be issued to the system simulation engine respectively, where the multiple control policies may be approximate control policies, for example, the multiple control policies are algorithm parameters that adjust an IP layer of the base station to num _1, num _2, num _3, so, num _ N, so that the system simulation engine may drive the twin mobile communication system to simulate according to the multiple control policies in sequence and send each network performance knowledge map to the knowledgebase after the simulation is completed, so that the knowledgebase may learn a control effect of each control policy according to each network performance knowledge map, for example, learn the control effect of each control policy according to each user SINR value, it may be understood that the knowledgebase may screen out a user SINR value with a largest value from the multiple user SINR values, for example, the algorithm parameter corresponding to the user SINR value with the largest value is num _5, it can be understood that, in the foregoing management and control policies, the management and control policy that adjusts the algorithm parameter of the IP layer of the base station to num _5 may bring an optimal management and control effect, so that the knowledge agent may generate the optimized management and control policy according to the network performance knowledge graph corresponding to the policy, that is, generate the management and control policy with the optimal management and control effect and send the management and control policy to the network management and control entity, so that the network management and control entity may control the mobile communication system to execute a corresponding management and control action according to the optimized management and control policy.
In some embodiments, the "system simulation engine driving the twin mobile communication system to simulate according to the control policy and feeding back the network performance knowledge graph to the knowledge agent after the simulation is finished" in step S20 may include, but is not limited to, the following: the system simulation engine enables the twin mobile communication system to repeatedly execute the simulation tasks corresponding to the control strategy within a preset time period, records performance indexes output by the twin mobile communication system after the simulation tasks are executed each time, and generates a network performance knowledge graph according to the performance indexes and feeds the network performance knowledge graph back to the knowledge intelligent agent after the simulation is finished.
In order to improve the reliability of the management and control effect verification, a reasonable simulation time period can be preset, so that the system simulation engine can drive the twin mobile communication system to repeatedly execute the simulation task within a corresponding time length, and it can be understood that the twin mobile communication system can output one performance index after executing the simulation task each time, and therefore the system simulation engine can generate a network performance knowledge graph corresponding to the management and control strategy according to a plurality of performance indexes after the simulation is finished and send the network performance knowledge graph to the knowledge agent.
In some embodiments, the system simulation engine is further configured to update the channel model in the twin mobile communication system according to the knowledge-graph before causing the twin mobile communication system to perform the simulation task each time. In the mobile communication system, the frequency of change of the wireless channel between the user terminal and the access network is relatively high, for example, the wireless channel changes due to the movement of the user terminal, so that the system simulation engine can update the channel model of the twin mobile communication system according to the knowledge map before enabling the twin mobile communication system to execute a simulation task each time, so as to ensure the reduction degree of the twin mobile communication system to the actual mobile communication system in the process of verifying the control effect and improve the reliability of the verification of the control effect. For example, as shown in fig. 5, after the system simulation engine drives the twin mobile communication system to perform the simulation task, when the simulation time is not reached, the system simulation engine may update the channel model according to the knowledge map, and then enable the twin mobile communication system to execute the corresponding simulation task and record a performance index output by the simulation task, so that when the simulation time is reached, the system simulation engine may generate the network performance knowledge map of the management and control policy according to a plurality of performance indexes.
In some embodiments, as shown in fig. 6, after step S30, the method may further include, but is not limited to, step S40.
And step S40, when detecting that the network performance of the mobile communication system is degraded, controlling the mobile communication system to execute the corresponding management and control action according to the original management and control policy, wherein the original management and control policy is the management and control policy used before the mobile communication system is controlled according to the optimized management and control policy.
As can be seen from the foregoing, the network management controller may control the mobile communication system to execute the corresponding management and control action according to the optimized management and control policy, but this process requires a long time, so in order to improve the reliability of the embodiment of the present application, the network management controller may monitor the network performance change of the mobile communication system, and when the network performance change is detected, the network management controller may control the mobile communication system to execute the corresponding management and control action according to the original management and control policy again, so as to recover the network performance of the mobile communication system.
An embodiment of the present application further provides a network management controller, as shown in fig. 7, including a processor and a memory, where the memory is used to store a computer program; the processor is used for executing the computer program and realizing any mobile communication system management and control method provided by the embodiment of the application when the computer program is executed.
It should be understood that the Processor may be a Central Processing Unit (CPU), and the Processor may be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program causes the processor to implement any one of the mobile communication system management and control methods provided in the embodiment of the present application.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable storage media, which may include computer readable storage media (or non-transitory media) and communication media (or transitory media).
The term computer-readable storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
For example, the computer readable storage medium may be an internal storage unit of the network management entity described in the foregoing embodiments, such as a hard disk or a memory of the network management entity. The computer readable storage medium may also be an external storage device of the network management entity, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the network management entity.
While the invention has been described with reference to specific embodiments, the scope of the invention is not limited thereto, and those skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the invention. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for managing and controlling a mobile communication system, comprising:
sending a knowledge graph spectrum stored in a knowledge agent to a system simulation engine in a twin mobile communication system to enable the system simulation engine to configure the twin mobile communication system according to the knowledge graph, wherein the twin mobile communication system is a simulation system of the mobile communication system;
receiving a control strategy generated by the knowledge agent and issuing the control strategy to the system simulation engine so that the system simulation engine can drive the twin mobile communication system to simulate according to the control strategy and feed back a network performance knowledge graph to the knowledge agent after the simulation is finished, wherein the network performance knowledge graph is used for enabling the knowledge agent to generate an optimized control strategy;
and receiving the optimized management and control strategy sent by the knowledge agent, and controlling the mobile communication system to execute corresponding management and control actions according to the optimized management and control strategy.
2. The method of claim 1, wherein the knowledge-graph comprises a radio environment knowledge-graph, a radio network element knowledge-graph, a network management knowledge-graph, and a user terminal knowledge-graph;
the twin mobile communication system comprises a plurality of twin communication devices, a twin air interface, a terminal motion model and a service model, wherein the twin air interface comprises a channel model and an antenna model;
wherein the system simulation engine configures the twin mobile communications system according to the knowledge-graph, including:
configuring software algorithm parameters of the plurality of twin communication devices according to the wireless network element knowledge graph,
Configuring hardware parameters and software algorithm policies of the plurality of twin communication devices according to the network management knowledge-graph,
Configuring the channel model according to the wireless environment knowledge graph,
Configuring the antenna model according to the network management knowledge graph and
and configuring the terminal motion model and the service model according to the user terminal knowledge graph.
3. The method of claim 1, wherein the knowledge graph stored in the intellectual property body is generated by the intellectual property body according to operation and maintenance data stored in a storage system in the mobile communication system.
4. The method according to any of claims 1-3, wherein the twin mobile communication system further comprises an environmental similarity contrast module configured to: after the system simulation engine configures the twin mobile communication system, determining the degree of reduction of the twin mobile communication system to the mobile communication system according to the same communication characteristics of the mobile communication system and the twin mobile communication system, and updating the twin mobile communication system according to the knowledge graph when the degree of reduction is detected to be lower than a preset threshold.
5. The method of claim 1, wherein the system simulation engine drives the twin mobile communication system to simulate according to the management and control strategy and feeds back a network performance knowledge graph to the knowledgeagent after the simulation is finished, and comprises the following contents:
the system simulation engine enables the twin mobile communication system to repeatedly execute the simulation tasks corresponding to the control strategy within a preset time period, records performance indexes output by the twin mobile communication system after the simulation tasks are executed each time, and generates the network performance knowledge graph according to the performance indexes and feeds the network performance knowledge graph back to the knowledge agent after the simulation is finished.
6. The method of claim 5, wherein the system simulation engine is further configured to update a channel model in the twin mobile communication system according to the knowledge-graph before causing the twin mobile communication system to perform the simulation task each time.
7. The method according to claim 1, after controlling the mobile communication system to perform the corresponding policing action according to the optimized policing policy, comprising:
and when detecting that the network performance of the mobile communication system is deteriorated, controlling the mobile communication system to execute the corresponding control action according to an original control strategy again, wherein the original control strategy is the control strategy used before the mobile communication system is controlled according to the optimized control strategy.
8. A network management controller is characterized by comprising a processor and a memory;
the memory for storing a computer program;
the processor for executing the computer program and implementing the mobile communication system management and control method according to any one of claims 1 to 7 when executing the computer program.
9. A management and control system comprising the network management controller, the knowledge agent, the mobile communication system, and the twin mobile communication system according to claim 8.
10. A computer-readable storage medium, characterized in that a computer program is stored which, when executed by a processor, causes the processor to implement the mobile communication system management method according to any one of claims 1 to 7.
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| CN111182556B (en) * | 2019-12-31 | 2022-09-30 | 中国电建集团河南省电力勘测设计院有限公司 | Wireless network planning design method based on intelligent agent |
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