449 results about "G-network" patented technology

The invention relates to the technical field of power distribution operation and maintenance management, and discloses an intelligent power distribution operation and maintenance management system based on 5G transmission. The system comprises a 5G real-time acquisition module, a multi-dimensional feature fusion module, a dynamic topology generation module, an anomaly propagation analysis module and a strategy optimization feedback module. The 5G real-time acquisition module acquires operation state data streams such as current and voltage waveforms, an equipment temperature sequence and environment monitoring indexes of the power distribution equipment through a 5G network; the multi-dimensional feature fusion module is used for separating equipment state features, calculating mutual information amount and generating equipment state feature tensors; the dynamic topology generation module constructs an association intensity matrix according to the feature tensor, and generates a hierarchical connection path and a dynamic equipment topological graph; the abnormal propagation analysis module extracts a state fluctuation sequence, identifies an abnormal transmission path and marks a core propagation node; and a strategy optimization feedback module generates a maintenance strategy priority queue according to the dynamic topology map, and feeds back an execution result to update the dynamic topology map, so that the intelligence and accuracy of power distribution operation and maintenance management are improved.

The application discloses a 5G network slice access control method based on service type, which comprises the following steps: 1) in a 5G network supporting multiple network slices, the type of a newly arrived service is judged, and the service is divided into a time delay sensitive service and a non-time delay sensitive service; if the service is the time delay sensitive service, step 2) is executed; if the service is the non-time delay sensitive service, step 3) is executed; 2) a bearing slice of the time delay sensitive service is selected; 3) a bearing slice of the non-time delay sensitive service is selected; 4) the next service needing transmission is waited for, and step 1) is executed. The application can minimize the time delay of the time delay sensitive service, realize the relative fairness of the time delay of various services, minimize the transmission waiting time of the non-time delay sensitive service, and improve user perception.

The invention relates to the field of network communication, and discloses a multi-source heterogeneous network data cooperative transmission method based on dynamic multi-dimensional evaluation and intelligent disaster recovery, which comprises the following steps: collecting system network parameters of a 5G network and a long-distance wired network in real time through a software definition interface module; performing weighted evaluation on the acquired system network parameters based on a dynamic link selection engine, the evaluation dimensions including real-time bandwidth, transmission delay and current link traffic, and generating an optimal communication link combination scheme; carrying out fragmentation and protocol adaptation on the data by adopting a general packaging framework and an intelligent label technology; distributing multi-path parallel transmission according to a priority strategy; at a receiving end, data recombination and disaster recovery supplementary transmission are realized through network coding and multi-path cooperation; and the evaluation weight is dynamically optimized in combination with reinforcement learning. According to the invention, the problems of rigid link selection, low protocol conversion efficiency and insufficient disaster tolerance in the prior art are solved.

The invention relates to the technical field of network capability scheduling, in particular to a 5G network dynamic security capability scheduling method based on deep learning. The method comprises the following steps: in a 5G network operation process, continuously collecting state parameters of network slices, and constructing a security situation data sequence; performing feature correlation analysis on the security situation data sequence, extracting security feature factors reflecting security situation changes, and generating a security risk judgment signal according to the security feature factors; when the safety risk judgment signal reaches a preset triggering condition, determining the scheduling priority and the distribution proportion of the safety protection unit according to the risk intensity and the resource occupation distribution; according to the invention, through 5G network dynamic security capability scheduling, security capability adaptive scheduling based on dynamic situation awareness is realized, and risk determination precision and resource allocation coordination are significantly improved.

The invention relates to the technical field of communication networks, in particular to a dynamic resource allocation method and system for an industrial 5G network. The method comprises the following steps: acquiring industrial terminal data; identifying network congestion nodes based on industrial terminal data; detecting a link congestion fault according to the network congestion node, and determining a bandwidth utilization rate; allocating spectrum resources based on the bandwidth utilization rate; performing frequency spectrum slicing on the frequency spectrum resources, and determining a flow load amount; adjusting load balance according to the traffic load, and generating a load resource report; dynamically adjusting time slot allocation by using a load resource report, and determining a task priority; task scheduling simulation is executed according to the task priority, and if congestion occurs, a congestion snapshot is stored; reducing scheduling conflicts according to the congestion snapshots, releasing bandwidth resources, and determining available network slice capacity; power resources are dynamically adjusted based on available network slice capacity. The bandwidth utilization rate and the task scheduling efficiency of the industrial 5G network are improved based on the communication network technology.

The invention relates to the technical field of network slice resource allocation, in particular to a 6G intelligent load balancing and fault self-healing method based on AI and network slices, which comprises the step of building an AI decision-making layer model architecture, a self-adaptive optimization mechanism, a resource dynamic scheduling mechanism and a strategy execution guarantee architecture. According to the method, the network load trend is predicted in real time through the AI technology, the resource allocation between the slices is dynamically adjusted, and the problem of low resource utilization rate caused by static allocation and periodic adjustment is solved. Meanwhile, an automatic fault detection and recovery mechanism is designed, when a node fault is detected, standby resource takeover can be quickly triggered, session continuity can be kept, the service interruption time is remarkably shortened, and the requirements of a 6G network for high reliability and low time delay are met.

The invention discloses a seamless switching method and system for a high-speed terminal of a ground-non-ground convergence network based on trajectory prediction and resource pre-reservation, and belongs to the technical field of space-ground convergence communication. The core of the method is that a switching area is accurately judged through bidirectional motion prediction of a terminal and an NTN node; a dynamic switching window is calculated in a self-adaptive mode by combining factors such as terminal speed and network time delay; intelligently selecting an optimal target link by using an AI enabled link scoring model; and cooperative pre-reservation and uplink and downlink synchronization of resources are completed before the window. The method has the advantages that the problem of failure of traditional RSRP judgment in an NTN dynamic environment is solved, the switching success rate and prediction accuracy in a high-speed moving scene are remarkably improved, the service interruption time and signaling overhead are greatly reduced, the continuity and reliability of communication are effectively guaranteed, and the method is suitable for large-scale popularization and application. The method is suitable for high-dynamic service scenes such as intelligent network connection vehicles and unmanned aerial vehicles in a 6G network.

A communication system is disclosed in which a number of procedures may be performed between user equipment, a base station, and / or the core network in the context of network slicing. The procedures support, for example efficient configuration of paging areas, roaming, access restriction, mobility, setting up of dual mode connectivity, connection re-establishment, efficient paging and slice selection.

The invention relates to the technical field of distribution network management, in particular to a distribution network management electricity meter state analysis method and system. According to the technical scheme, the distribution network management electricity meter state analysis method comprises the following steps that S1, multiple layers of edge computing nodes are deployed in a power distribution network, first-level nodes are deployed in a power distribution station, second-level nodes are deployed in an electricity meter concentrator, and computing resource distribution of the edge nodes is dynamically adjusted based on electricity meter distribution density and real-time loads; s2, through a collaborative acquisition mechanism of the first-level node and the second-level node, acquiring operation data of the electric meter in real time; and S3, transmitting the classified and marked data by adopting a multi-modal compression strategy: compressing the periodic monitoring data by using difference value coding, and extracting the sudden abnormal data by using a feature abstract. By constructing a multi-level edge collaborative acquisition mechanism and a 5G network slice transmission channel, the real-time bottleneck of traditional manual inspection and fixed-period acquisition is broken through.

Systems and automated processes are described to provide collection of wireless network status data, such as a 5G network, and to automatically respond to queries regarding the performance of the network. Systems and automated processes may, in response to a request for network performance information, obtain performance and static data from network data sources, analyze the static data to generate validated site data, apply a KPI formula to the performance data to generate KPI data, and generate a network performance report based on the validated site data and KPI data. In addition, the systems and automated processes may use an appropriate machine learning model from a library of models to determine recommended actions to increase network performance and may automatically implement such actions. A top offender system may be implemented to analyze the status data to determine the network elements having the largest negative impact on network performance.

Systems and automated processes are described to provide collection of wireless network status data, such as a 5G network, and to automatically respond to queries regarding the performance of the network. Systems and automated processes may, in response to a request for network performance information, obtain performance and static data from network data sources, analyze the static data to generate validated site data, apply a KPI formula to the performance data to generate KPI data, and generate a network performance report based on the validated site data and KPI data. In addition, the systems and automated processes may use an appropriate machine learning model from a library of models to determine recommended actions to increase network performance and may automatically implement such actions. A top offender system may be implemented to analyze the status data to determine the network elements having the largest negative impact on network performance.

The invention provides a VR game data synchronous transmission method based on a 5G network, and the method comprises the steps: obtaining a multi-type data stream generated during the operation of a VR game, extracting scene rendering data and player interaction data from the multi-type data stream, separating a feature value of each data type, and obtaining a data priority sequence; analyzing the real-time requirements of the scene rendering data and the interaction data according to the data priority sequence, and judging a key data packet which needs to be transmitted immediately; the method comprises the following steps: monitoring a current bandwidth fluctuation condition through a network transmission layer, calculating available bandwidth and delay parameters from network state data acquired in real time, and obtaining a resource allocation reference value in a dynamic scene; and for high-priority data packets, a dynamic resource allocation algorithm is adopted to adjust a transmission queue sequence, a resource allocation reference value is corrected through a bandwidth fluctuation parameter, and a transmission time slot allocation scheme of the key data packets is determined.

As described herein, a system, method, and computer program are provided for managing quality of 5G network slice services. A latency issue in a 5G network is detected. Information associated with the 5G network is collected. The information is analyzed to determine a network slice provisioned in the 5G network having a quality requirement that is not met as a result of the latency issue. The network slice is reengineered, using the information associated with the 5G network. The reengineered network slice is deployed in the 5G network.

The invention provides a remote crusher cluster intelligent scheduling method and system based on 5G communication, and relates to the technical field of wireless communication, and the method comprises the steps: collecting the real-time load, feeding intensity, yield, conveying equipment flow and other data of crushers through a 5G network; a fluid dynamic model containing upstream-downstream material transportation time delay parameters is adopted in the central dispatching server, and downstream material input is predicted in combination with the material attribute tags; and generating a target production rhythm curve with a time index, forming a time-related cooperative control instruction, and issuing the time-related cooperative control instruction to an equipment end controller for synchronous execution. According to the method, operation parameters are adjusted in a self-adaptive mode according to feeding strength differences of different cavity types, the yield and mechanical loads are balanced, and the instantaneous accumulation and overload risks are reduced; the execution precision and robustness under network jitter are improved through mechanisms such as time slot alignment, time delay compensation and sub-lattice point protection; and the productivity utilization rate is increased, equipment abrasion is reduced, and production continuity and safety are guaranteed.

The embodiment of the invention provides an LLM-based 6G network automatic security processing method and system. The method is applied to the field of network security intelligent protection, and comprises the following steps: acquiring a network data stream, generating a structured log, extracting features, inputting the features into an intrusion detection model to identify attack behaviors, performing format conversion on a result to generate an LLM model, inputting the LLM model, and reasoning to obtain a network security disposal strategy. And extracting key fields, performing structured packaging, uploading the key fields to a block chain to complete evidence storage and integrity verification, and finally executing corresponding security control operation according to a strategy. According to the scheme, intelligent identification and automatic processing of network attacks are realized, after key fields are extracted, the structured strategy data are generated and uploaded to the block chain system for evidence storage and verification, traceability and data integrity of the processing process are ensured, network defense control which is automatic, high in security and timely in response can be realized, and the network attack processing efficiency is improved. And the intelligent and credible level of network security management is obviously improved.

The invention relates to the technical field of information communication, and discloses a 5G network slice resource scheduling method for a power distribution network, and the method comprises the steps: firstly collecting the geographic coordinates and priority labels of a service request, carrying out the regional division of a service based on the coordinates, and determining the cluster center of each region; then combining the priorities and the areas to which the requests belong, carrying out hierarchical sorting on all the requests to generate a global scheduling sequence; for each request in the sequence, calculating a path distance to each network resource node according to the coordinate of the request and the cluster center, and selecting a shortest path node as a target resource node; and finally, allocating resource quotas from the resource pool of the target node in sequence. According to the 5G network slice resource scheduling method provided by the invention, the resource matching accuracy and locality are effectively improved, the service transmission delay is reduced, the network flow space distribution is optimized, and the more efficient and reliable bearing of the power distribution network service is realized.

The invention discloses a method for automatically inspecting equipment in intelligent manufacturing, which comprises the following steps of: 1, deploying edge computing nodes, combining with 5G network slices, cleaning and compressing inspection data in real time, dividing priorities, performing low-delay transmission on key data through a special bandwidth, and locally caching or filtering non-key data; 2, developing a controller based on the software defined network, monitoring a link state, introducing a reinforcement learning algorithm, and dynamically optimizing a transmission path; 3, deploying a TinyML framework at an equipment end, integrating a model compression technology to operate a lightweight AI model, and combining sensor data to perform real-time early warning and support offline analysis; 4, constructing an incremental learning framework, dynamically updating model parameters through knowledge distillation, and only adjusting part of parameters to adapt to state change; and step 5, an analysis result is fed back to the system by using a message queue, and a patrol strategy is dynamically adjusted in combination with a rule engine to form a closed-loop optimization mechanism of data acquisition-transmission-analysis-decision.

Methods and systems are provided for assigning one or more Virtual Network Function (VNF) instances, or slices, to devices, and for monitoring each change of state associated with the slices. Embodiments include applying an Advanced Security Control (ASC) protocol to verify devices for each request for access to a slice, to establish a zero trust measurement with respect to a network, such as a 5G network. In embodiments, a blockchain is associated with each slice and stored in a distributed ledger, for example to allow rapid access to network slice and device information if a slice will be re-instantiated.

The invention provides a power distribution communication network topology optimization system based on the Internet of Things, and relates to the technical field of power Internet of Things, which obtains and fuses topology and fault state data from a power grid SCADA system and slice performance and bearer network state data from a 5G network management system in real time. The system can construct a fusion state vector comprehensively describing the power grid-communication network joint operation situation. The vector is input into an intelligent decision-making model based on imitation-reinforcement learning training so as to generate an optimal action instruction in real time. The instructions are accurately analyzed into dynamic adjustment commands for 5G network slice resources and routing policy change instructions for key service flows. According to the concept, the problems that in an existing scheme, a communication network perceives the power grid state blindly, and slice resource configuration is rigid are solved, communication resources can be instantly and intelligently inclined and reconfigured according to the real-time and specific requirements of the power grid, and the stability and safety of power grid operation are improved.

The invention relates to the technical field of indoor 5G network optimization, and discloses an indoor 5G network optimization system based on ray tracing, which is characterized in that a network signal state parameter set is dynamically acquired through a signal parameter acquisition module, a signal coverage risk is judged, and a collaborative analysis instruction is triggered to execute a ray tracing analysis module and an interference characteristic analysis module; and respectively acquiring a propagation stability index and an interference evaluation value. And the multi-source fusion judgment module receives the two values to carry out cooperative analysis on the network coverage adaptability, and generates antenna adjustment and power optimization signals. And the optimization parameter generation module is matched with the strategy to generate antenna angle adjustment and power correction parameters. The system further comprises a coverage coupling analysis module monitoring signal and building structure coordination and a dynamic feedback execution module to form a closed-loop control link, and intelligent optimization of an indoor 5G network is achieved.

The invention relates to the technical field of network communication, in particular to an intelligent visual edge gateway control method based on a 5G network. According to the method, real-time transmission and timely control of edge gateway information are achieved through the 5G network, meanwhile, the operation state of the edge gateway is visually and comprehensively mastered through the information, timely finding and processing of problems are facilitated, the visual quality and the data transmission quality are ensured along with channel communication quality evaluation and analysis of the 5G network, and the service life of the edge gateway is prolonged. The resource allocation is dynamically adjusted in an information progressive mode, the transmission timeliness of priority data is guaranteed during channel load fluctuation, the problem that a fixed scheduling strategy is poor in adaptability is solved, meanwhile, the operation state information of the edge gateway is further analyzed, and the service life of the edge gateway is prolonged. According to the method, reasonable fault management can be carried out according to hardware or software faults of the edge gateway, namely, the hardware faults and the software faults are analyzed, so that the faults of the edge gateway can be found and processed in time, manual intervention is reduced, and the reliability of the system is improved.

The invention discloses a multi-access network intelligent selection system and method in a 5G network environment, and the system comprises a multi-network state sensing module, a service feature recognition module, an intelligent access decision module, a network switching control module, and a strategy updating and learning module. According to the present service type and service quality demand dynamic optimization, communication performance and user experience are considered, an access decision-making mechanism with an adaptive learning capability is constructed, experience can be accumulated along with time, a strategy can be continuously optimized, the frequency and cost of network switching are controlled, the communication continuity is ensured, unnecessary switching risks are reduced, and the network switching efficiency is improved. The method is suitable for various actual scenes such as a 5G mobile terminal, a vehicle-mounted communication device and an industrial terminal, the communication performance and the overall use experience of the terminal device in the 5G environment under the multi-network access condition are effectively improved, and a basic support is provided for achieving heterogeneous network convergence and intelligent communication.

The invention relates to the field of communication, and discloses an intelligent traffic scheduling optimization method, device and equipment and a storage medium, and the method is used for 5G network intelligent traffic scheduling optimization. The method comprises the following steps: receiving a service request, analyzing the service request to obtain a 5G standard service type, an application scene and a 5G network slice identifier, then obtaining an SLA parameter corresponding to the service request and a candidate link required by service transmission, and converting the SLA parameter into an SLA preference vector; acquiring global data of the candidate link, and predicting by using the network state prediction model to obtain a predicted network state of the candidate link; the SLA preference vector is used as optimization target guidance, the predicted network state is used as a constraint condition, and a global optimization routing strategy is calculated through a multi-target optimization algorithm; and generating a control message packet based on the global optimization routing strategy, issuing the control message packet to the network forwarding equipment, and adjusting parameters of the network state prediction model and the multi-objective optimization algorithm based on the actual performance data after execution.

The invention relates to a 5G + TSN-based industrial equipment real-time synchronous communication method and system, and the method comprises the following steps: carrying out the clock calibration of industrial equipment through a time synchronization module, obtaining equipment clock data, adding a timestamp, and forming timestamp equipment data; and performing time slot allocation on the 5G network based on the data to generate a time slot allocation table, and performing traffic scheduling on the TSN network according to the time slot allocation table to obtain scheduling configuration information. And performing priority marking on the information to obtain priority data, and calculating an optimal transmission path of the 5G network according to the priority data. And transmitting and confirming the priority data through the path, and generating transmission confirmation information. And a synchronization control instruction is generated based on the confirmation information, and is directionally issued to each industrial device, so that high-precision time synchronization control of multi-device cooperative operation is realized, and the technical problems that time faults occur on an end-to-end communication path and multi-device cooperative control is seriously influenced due to clock asynchronization between a 5G network and a TSN network are solved.

The present disclosure relates to a system (100) and a method for switching user equipment(s) (UEs) between communication networks (4G, 5G, and 6G). The method includes detecting an outage (service failure or interruption in service) in a network based on a reference signal received power (RSRP), a reference signal received quality (RSRQ), and a signal-to-interference-plus-noise ratio (SINR) and switching the UE from a first network to a second network. On detecting the outage, a mobility management entity (MME) queries a home subscriber server (HSS) for the UE usage type. If the user is 4G-only, the MME selects 4G network and if the user is migrated to 4G / 5G combination core, then the MME selects the 5G network. A circle-wise global flag in the HSS return “4G” for the MME query regarding the UE usage type, so the MME selects the 4G core and the user will move to the 4G network.

The invention relates to the technical field of communication networks, in particular to an intention-driven satellite-ground convergence network on-demand arrangement system and method, and the method comprises an intention input layer which is used for receiving a multi-mode intention of a user; the intention analysis layer is used for analyzing the intention of the user to generate a recognizable network strategy; the arrangement control layer comprises a design state and an operation state; wherein the design state is used for dynamically generating a resource arrangement strategy based on an identifiable network strategy, and verifying the feasibility of the resource arrangement strategy in the digital twin network; the running state is used for generating an executable scheme based on the verified resource arrangement strategy; and the infrastructure layer comprises a satellite-ground unified atomic power abstraction module which is used for abstracting heterogeneous resources into standardized atomic power and executing an executable scheme. The scheme aims to provide a brand-new intention-driven satellite-ground fusion network arrangement architecture with dynamic generation, thorough decoupling and active prediction capabilities, so that the technical problem that complexity and dynamics of a 6G network cannot be handled at present is solved.

The invention discloses a multi-network integration intelligent route selection method and system based on multi-dimensional dynamic evaluation, and the method comprises the following steps: S1, network communication hardware of equipment collects the signal intensity and signal quality parameters of GEO, LEO, Beidou short messages and 4G / 5G network links in real time, and transmits the parameters to an intelligent route selection decision engine module; by introducing the multi-dimensional dynamic weight evaluation model and the intelligent route selection decision engine, parameters such as signal strength and signal quality of multiple network links such as GEO, LEO, Beidou short messages and 4G / 5G can be monitored in real time, the optimal network link is automatically selected as an internet access channel in combination with data size and tariff standards, and the network access efficiency is improved. Therefore, optimal configuration of network resources is realized, the quality and efficiency of network connection are improved, and the use cost of a user is reduced.

The invention discloses a time synchronization method, a time synchronization system and a storage medium, and the method comprises the steps: receiving and fusing multi-source time signals at the same time, and obtaining a local time reference signal; calculating the frequency compensation amount of a local clock source in real time based on an LSTM model trained by using a local time reference signal; detecting whether the time signal is available, and determining to switch an atomic clock taming mode or a timekeeping mode based on a detection result; inserting a timestamp with femtosecond precision for the initial data message through the PIC to obtain a target data message; and sending the time synchronization information and the target data message to a 6G network node through a precision time protocol of the FPGA chip. According to the invention, on the basis that the satellite signal is taken as a time reference, two conditions that the satellite signal is available and unavailable are considered, and a local clock source and photon time service are adjusted in combination with a multi-source satellite signal fusion result, so that the time synchronization precision is improved, and the 6G network requirement is met.

The invention provides a method for allocating resources among 5G network slices, which comprises the following steps of: firstly, calculating the bandwidth occupied by each service in each network slice based on the number of physical resource blocks occupied by the service and the bandwidth of a single resource block; calculating the theoretical capacity capability of each service according to the Shannon sampling theorem, and calculating the actual service capability at the current moment based on the service congestion rate; calculating the idle bandwidth capability of each slice based on the number of idle resource blocks of each slice and the mathematical expected value of the single resource block capability; calculating the controllable bandwidth capability of each slice based on the service busy ratio and the idle bandwidth capability of each slice; and finally, normalizing the controllable bandwidth capability of each slice to serve as a slice resource allocation priority index for resource allocation.

A communication system is disclosed in which a number of procedures may be performed between user equipment, a base station, and / or the core network in the context of network slicing. The procedures support, for example efficient configuration of paging areas, roaming, access restriction, mobility, setting up of dual mode connectivity, connection re-establishment, efficient paging and slice selection.