1272 results about "Service flow" patented technology

The invention provides a power distribution network symbiotic simulation system and method based on digital twinning. The system comprises a power distribution network digital twinning simulation platform, a cloud edge hierarchical deployment collaborative architecture and a power distribution network terminal. The digital twinborn simulation platform for the power distribution network comprises a data layer, a model layer, a service layer and an application layer which are covered in sequence by taking a cloud platform as a bottom, and the cloud edge hierarchical deployment collaborative architecture performs hierarchical deployment according to different service functions of the power distribution network. According to the invention, through the constructed full-attribute isomorphic power distribution network digital twinborn simulation platform and the cloud edge hierarchical deployment collaborative architecture, the fusion demand of multi-scene multi-service flow is fully considered, through the symbiotic simulation technology, dynamic feedback and collaboration between the simulation system and a real system are realized, and the highly integrated and collaborative simulation system has the advantages of high simulation efficiency and high reliability. Various changes in the power distribution network can be quickly responded, and a solid guarantee is provided for safe and efficient operation of the power distribution network.

The invention provides a self-adaptive network topology dynamic reconstruction method and system based on deep reinforcement learning, and relates to the technical field of deep reinforcement learning, and the method comprises the steps: obtaining the topology state information, service flow distribution information and historical reconstruction records of a current network; extracting topological correlation characteristics among nodes through graph convolution operation, and generating fusion state representation in combination with service flow information; inputting the fusion state representation into a deep reinforcement learning model to identify bottleneck nodes and redundant links, and outputting a reconstruction action candidate set; searching and evaluating the long-term cumulative income of the candidate actions through a Monte Carlo tree, and screening an optimal reconstruction action sequence; a graph coloring algorithm is utilized to allocate time slots and process resource conflicts, and a resource-feasible topology adjustment scheme is generated; and extracting a network evolution rule through tensor decomposition, and constructing a topological optimization association mapping graph. According to the method, the network bottleneck can be intelligently identified, the network topology structure is dynamically optimized, and the network performance and the resource utilization rate are effectively improved.

The invention relates to the technical field of communication networks, and discloses a service channel time slot allocation method, which comprises the following steps of: 1, acquiring network data in real time from network equipment, the network data comprising bandwidth utilization rate, delay, packet loss rate and service flow type; 2, predicting future network flow fluctuation through a long-short-term memory network model based on historical flow data and real-time network data; and step 3, dynamically adjusting the allocation of time slot resources according to the network flow fluctuation prediction result, and preferentially allocating the time slot resources for high-priority services. According to the method, the dynamic adjustment of the time slot resources is realized by combining the flow prediction of the LSTM model and the Q-learning reinforcement learning algorithm, so that the system can flexibly allocate the resources according to the actual network load condition, the resource waste is reduced, the utilization efficiency of the bandwidth is improved, and the utilization rate of the overall network resources is remarkably improved especially under the condition of high network load.

Aspects relate to core network entities that: establish a session including at least one of: application data unit (ADU) detection rules, or ADU handling rules related to a detection of ADUs in a user plane, and determine, for one or more quality of service (QOS) flows, whether ADU awareness applies based on an application of the ADU detection rules, or the ADU handling rules; and transmit a request to create a session that supports ADU-based QoS flows, negotiate at least one of: ADU-based QoS policies, or ADU QoS rules applicable to the session, and receive an acknowledgment of creation of the session in response to completing the negotiating. A radio access network entity conveys, during a session, one or more ADUs to a user equipment via a user plane in compliance with ADU-based QoS policies associated with at least one ADU aware QoS flow.

The invention discloses a mobile communication load collaborative scheduling system and method based on energy efficiency perception, and belongs to the technical field of mobile communication, energy consumption data of each functional module in a base station and external network environment parameters are collected in real time through a multi-source sensor network in the base station, and a dynamic energy efficiency map is generated; based on historical energy efficiency data and real-time load characteristics, constructing an energy efficiency construction prediction model, and predicting an energy efficiency hotspot area; based on the historical movement track of the user and the spatial and temporal distribution characteristics of the service flow, the movement trend of the user and the change trend of the service flow are analyzed, and in combination with an energy efficiency prediction model, a potential overload base station is identified, and overload early warning is triggered; after receiving the early warning information, screening candidate target base stations according to a preset radius by taking the overload base station as a core; and generating a load idle list in a descending order according to the real-time energy efficiency ratio of the candidate base station, and performing energy efficiency sensitivity priority grading on the to-be-migrated service, thereby generating a collaborative scheduling strategy and executing load migration.

The invention discloses a P4 switch processor core-oriented multi-service traffic packet scheduling method, which mainly comprises the following steps of: proposing a feature extraction method based on a statistical interval and Sketch, integrating data packet time correlation and traffic dynamic change, optimizing a Bloom filter conflict detection mechanism, and improving the adaptability and accuracy of an algorithm in a limited resource environment; a decision tree model is combined with scheduling, a decision tree is reconstructed to adapt to an operation mode and a data processing requirement of a P4 switch, and high-precision service flow classification under linear speed operation is ensured; a packet scheduling method AD-PIFO is designed based on a variable priority, the forwarding priority of a data packet is dynamically adjusted, the QoS requirements of different services are met, and the overall performance and efficiency of the switch are improved. The method is outstanding in high-priority traffic throughput and low-delay performance, is superior to similar algorithms in medium-low priority traffic throughput, is stable and effective under different load conditions, is reasonable in extra time overhead of data packet transmission, and is widely applied to SDN network optimization data packet scheduling scenes.

The invention relates to the technical field of resource allocation, in particular to a unified resource pooling management method for multiple computing power sources of an unmanned aerial vehicle platform, which comprises the following steps of: analyzing an unmanned aerial vehicle service flow to obtain subtask nodes and dependency relationship edges, and measuring and calculating the execution time of each subtask on different heterogeneous computing power units. According to the method, subtask nodes and dependency edges are obtained by analyzing the unmanned aerial vehicle service flow, the refined execution time of each subtask on a heterogeneous computing power unit is measured and calculated on the basis of task execution priority ranking, the actual consumed time of data transmission between tasks is clearly calculated, a complete heterogeneous computing power pool scheduling basic view is formed, and the scheduling efficiency of the heterogeneous computing power pool is improved. Therefore, the task execution efficiency and the resource scheduling accuracy are improved; meanwhile, in the resource allocation process, the real-time operation temperature and the calculation error rate of each computing power unit are continuously monitored, the dynamic health state is intelligently analyzed and calculated, the potential fault risk is recognized in time, and a pre-degradation control signal is actively triggered.

The invention discloses a cross-domain collaborative interface dynamic configuration method and device and a computer program product. According to the cross-domain collaborative interface dynamic configuration method, service flow priorities are determined by analyzing service layer data, and an initial interface configuration scheme is generated in combination with network state information. And when the initial scheme does not meet the transmission requirements, optimizing the interface parameters by adopting a dynamic programming algorithm, generating a new configuration scheme, and issuing the new configuration scheme to the target network management system. In the service switching process, network performance is monitored in real time, interface parameters are dynamically optimized and updated to a network management system, and intelligent management of service flow and efficient utilization of network resources are achieved. The method can adapt to different manufacturer devices and network levels, guarantees the service quality of cross-domain services, and improves the operation efficiency and reliability of an electric power communication network.

The invention discloses an intelligent user permission conflict detection method and system, and relates to the field of electrical digital data process.The method comprises the steps that a service flow diagram is constructed based on historical records; extracting a service flow direction sequence of the permission roles from the service flow direction graph, and calculating service association degrees among the permission roles according to the service flow direction sequence; grouping and clustering the authority roles according to the business association degree to obtain a plurality of authority role clusters; calculating a service boundary value of each permission role cluster; determining a target permission role cluster to which the target permission role belongs from a plurality of permission role clusters; calculating the business association strength between the permission role currently owned by the target user and the target permission role; when the business association strength exceeds a business boundary value, generating a first permission allocation control instruction; and when the business association strength does not exceed the business boundary value, generating a second permission allocation control instruction. The method and the device are used for solving the problem of authority conflict in a newly-added business scene, so that the security of the system is improved.

The invention provides a multi-level service priority dynamic scheduling simulation method and device, a medium and a product. The method comprises the following steps: constructing a priority label system; establishing a dynamic binding relationship between the service flow and the priority label; when a service layer generates a data packet, embedding a priority label for the data packet based on the dynamic binding relationship; extracting a priority label carried by the data packet on a protocol stack MAC layer, and ensuring that the priority label is unvarnished to a lower layer protocol in a lossless manner; and based on the priority labels carried by the extracted data packets, classifying the data packets into logic queues with corresponding priorities, and executing a differentiated scheduling strategy. The method can adapt to diversified requirements of data services of different types and priorities for network resources, effectively improves the simulation model accuracy, improves the simulation experiment efficiency and simulation real-time performance and reliability in a multi-service priority 5G communication network simulation scene, more accurately reflects the performance of a real network, and improves the simulation experience of the 5G communication network. And meanwhile, the simulation platform has higher expansibility and flexibility.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

The invention provides an intelligent computing fusion network routing system and a routing method thereof. The system comprises an entrance gateway, a routing forwarding node, a computing node and a computing network controller, the computing network controller is used for carrying out path selection and computing resource allocation in combination with a real-time network state and load information of the computing node, dynamically generating and updating a computing network routing table through a computing network fusion routing algorithm, and issuing the computing network routing table to the entry gateway and the routing forwarding node; and the entry gateway receives and stores the computing network routing table issued by the computing network controller as a data stream access point, receives a computing power data stream which is input from the outside and carries a computing power service request, executes computing power routing table matching according to the computing power service request, and forwards the computing power data stream to a proper routing forwarding node according to a matching result. According to the invention, by optimizing the joint scheduling of the computing power service paths and the computing nodes, a plurality of paths of the anycast computing power routing and the weights of the paths are generated, the service flow level load balancing is realized, and the end-to-end time delay is reduced.

The invention belongs to the technical field of communication, and particularly relates to a directional traffic service guarantee method of a PCC self-intelligence network based on an AI agent. Comprising the following steps: an AI identifies a live broadcast application and issues a policy control and charging PCC rule; service experience detection: the NWDAF receives user flow data, and the NWDAF continuously monitors the experience quality of the live broadcast service; establishing a service awareness baseline: establishing the service awareness baseline for different live broadcast applications through AI learning: based on a user level signing protocol, analyzing experience class data of a service flow in combination with a network element; according to the experience class data analysis result of the service flow, when the service experience index is lower than the service awareness baseline, the definite positioning analysis is carried out, then a dynamic guarantee mechanism is triggered according to needs, and oriented dynamic QoS optimization is carried out on a user network. According to the invention, the problems of network congestion and network resource waste of the PCC self-intelligence network are solved.

The invention relates to the technical field of data processing, in particular to a load awareness and data dynamic layout method and system based on deep learning, and the method comprises the steps: collecting hardware load indexes of all nodes in a distributed cluster in real time, and carrying out the preprocessing of the hardware load indexes; based on the preprocessed hardware load index, calculating a comprehensive load score of each node through a weighted fuzzy logic algorithm; dividing load intervals according to the comprehensive load score and matching a predefined strategy combination; and dynamically adjusting a compression algorithm, a compression ratio and a fragment merging parameter based on the current service flow peak-valley state of the target data block and a matched predefined strategy combination, the service flow peak-valley state being determined through a request processing rate and response time. The objective of the invention is to realize dynamic and fine-grained load sensing and data layout.

The invention discloses a predictive topology-based satellite internet deterministic routing data plane migration method, which mainly solves the problem of data packet and service interruption during satellite switching in the prior art. According to the implementation scheme, service flow terminal equipment firstly sends an access request to an entrance edge node; the entry edge node calculates a tunnel path and resource reservation according to the request, performs service identification, encapsulates various identifiers into deterministic specific segment identifiers, and encapsulates the original data packet into an SRv6 data packet based on the tunnel path and the specific segment identifiers; when the service flow is transmitted in the satellite network, if a satellite is switched, service flow tunnel migration is carried out, and when a queue data packet exists in the switched satellite, queue cache migration is carried out. According to the invention, the forwarding of the service flow in the satellite switching process is not influenced, the flow interruption or transmission error caused by lack of information pre-synchronization in the traditional satellite switching is avoided, the priority transmission of the high-priority data packet is ensured, and the method can be used for data transmission between a ground terminal and a deterministic satellite network.

Example communication methods and apparatus are described. In one example method, a user plane network element obtains network status information of a to-be-monitored service flow. The network status information is used to determine a ratio of a quantity of data packets carrying a congestion experienced (CE) mark in at least one data packet of the to-be-monitored service flow to a quantity of the at least one data packet of the to-be-monitored service flow. The user plane network element adds, based on the network status information, the CE mark in the at least one data packet of the to-be-monitored service flow, and sends the at least one data packet in the to-be-monitored service flow to a terminal device. According to some embodiments, the user plane network element sends the network status information to the terminal, so that the terminal knows the network status in mobile network.

The present application relates to the technical field of network routing, and discloses a method and system for adaptively adjusting network routing, the method comprising: performing detection data packet transmission and hierarchical clustering on a network interface to obtain a path cluster set; performing double-circular matrix encoding on the path cluster set to obtain a routing path encoding set; constructing a spatiotemporal feature tensor based on the routing path encoding set, and performing tensor decomposition and feature pattern extraction to obtain a time-varying weight coefficient; performing sparse-aware proportional iterative optimization calculation based on the spatiotemporal feature tensor and the time-varying weight coefficient to obtain an optimal routing configuration scheme, thereby achieving differentiated processing of different business flows and improving network resource utilization efficiency.

The invention relates to the technical field of communication network security, in particular to a communication network security auditing method and system under multi-source heterogeneous data association, and the method comprises the steps: collecting network flow data and log data in a communication network in real time; distinguishing non-service flow data and signaling data (also called service flow data) from the collected network flow data; performing deep analysis and classification processing on non-service flow data, performing unified analysis and association analysis on log data, and performing protocol decoding and content analysis on signaling data; constructing a multi-source heterogeneous data association relationship analysis model, integrating non-service flow data, signaling data and log data, mining space-time association and causal relationship among the data by applying a machine learning algorithm, and constructing a network security situation map; and based on a multi-dimensional analysis result, automatically generating a security audit strategy matched with the multi-dimensional analysis result. According to the invention, accurate detection, real-time blocking and risk early warning of communication network security threats are realized, and the network security protection capability and the operation and maintenance efficiency are improved.

The invention provides a substation secondary system communication network adaptive topology reconstruction method, which comprises the following steps: modeling by adopting multi-scale time delay feature fusion, and accurately predicting protocol conversion time delay; designing a hierarchical fusion protocol conversion time delay control framework, wherein the framework comprises two-stage time delay control of feed-forward compensation and feedback adjustment based on a resource-time delay sensitivity matrix; proposing a protocol semantic dynamic cutting technology, and realizing time delay demand-based differential semantic processing through a performance-semantic tradeoff function; and constructing a topology reconstruction decision-making mechanism of end-to-end time delay perception, and comprehensively evaluating the influence of the candidate topology scheme on the key service flow time delay. According to the method, the protocol conversion time delay of key services in the multi-protocol environment of the transformer substation is reduced, and millisecond-level time delay guarantee and self-adaptive optimization of network topology are realized.

The invention provides a communication method and device, and belongs to the technical field of communication, in the method, a network element at a network side, such as a first network element, can obtain network congestion information of a service flow so as to determine the possibility of congestion of a current network and execute supervision. For example, after the network congestion degree is increased, if the possibility of network congestion has reached that an application side needs to adjust the transmission of the service flow to reduce the possibility, if the first network element determines the application side by monitoring the transmission of the service flow and adjusts the transmission of the service flow, the first network element determines the application side by monitoring the transmission of the service flow. If not, the transmission can be managed and / or controlled, so that network congestion is avoided, fairness between services is guaranteed, and the use experience of a user is guaranteed.

The invention discloses a message processing method and related equipment, a first communication device obtains a hash key value according to an obtained first message and obtains a first routing parameter of a flow corresponding to the first message, the first communication device determines a first path for sending the first message according to the hash key value and the first routing parameter, and the first path is used for sending the first message to the first communication device. And sending the first message through the first path. Therefore, when the first communication device senses that the grey fault occurs and then needs to forward the message, the first communication device only needs to use the routing parameter of the stream to which the message to be forwarded belongs and the hash key value in the message to be forwarded as the parameter of the hash routing to perform the hash routing; according to the method, the forwarding path of the message to be forwarded can be quickly switched when the gray fault occurs, so that the configuration work needing to be implemented for switching the path is simplified, the time overhead of switching the path is reduced, the path can be switched in time after the gray fault occurs, the recovery time of the service flow is short enough, and the influence of the gray fault on the service is reduced as far as possible.

A routing method for supporting differential service requirements in a satellite internet comprises the following steps: step 1, constructing multi-dimensional network state perception as a base layer which is responsible for collecting and quantifying physical states and logic states of a satellite network in real time, and obtaining objective network states and subjective QoS (Quality of Service) requirements of services; 2, generating a nonlinear adaptive weight driven by a service as a strategy layer, mapping an objective network state and a subjective QoS (Quality of Service) demand of the service, dynamically adjusting the value orientation of routing judgment, and generating a dynamic weight; and step 3, taking the dynamic cost routing decision as an execution layer, calculating the comprehensive cost based on the dynamic weight, and executing next hop selection and path maintenance, and through cooperative work of the dynamic cost routing decision, the comprehensive cost and the next hop selection and path maintenance, realizing intelligent path selection and high-reliability transmission for different service flows in a high-dynamic and resource-limited environment of the low-orbit satellite. According to the invention, while the routing computation overhead is effectively reduced, multiple requirements of differentiated services on low time delay and high reliability can be considered.

The embodiment of the invention discloses a soft bus power terminal heterogeneous interconnection method and system based on an Ethernet protocol stack. The method comprises the following steps: dynamically calculating fragment parameters according to the difference of different protocol stacks in heterogeneous network interconnection; based on a dynamic programming algorithm, generating a self-adaptive fragmentation scheme according to the input parameters, and forming an integrated fragmentation recombination framework; based on an intelligent decision-making mechanism, an optimal fragmentation strategy and a recombination mechanism are generated, a simulation platform is established, different network scenes and service flows are simulated, a simulation result of the simulation platform is combined with a result of the intelligent decision-making mechanism, and the effect of an intelligent decision-making algorithm is optimized. And transmitting and recombining the data packet by adopting an encryption and authentication mechanism. According to the scheme, the efficiency and the reliability of data transmission in the heterogeneous network are remarkably improved, the compatibility problem among different network protocol stacks is effectively solved, the fragmentation frequency during cross-network transmission is reduced, the time sequence and the integrity of data packets are ensured, and the processing overhead and the network delay are reduced.

The invention relates to an interaction method and device, computer equipment and a storage medium, and the method comprises the steps: determining a plurality of target intentions related to a user according to multi-mode information related to a target vehicle; a dialogue service flow is started, and the dialogue service flow comprises the steps that for each target intention in the multiple target intentions, an instruction corresponding to the target intention is sent to an application, to which an atomization service function used for achieving the target intention belongs, in the at least one application, so that the application calls the atomization service function used for achieving the target intention according to the instruction; and providing information for guiding user interaction for the user, wherein the information for guiding user interaction comprises a calling result corresponding to the atomization service function for realizing the target intention.

The invention discloses a communication network bandwidth resource visualized dynamic allocation method and system based on an SDN, and relates to the technical field of communication networks, and the method comprises the steps: obtaining the channel interference intensity, the spectrum occupancy rate and the service flow priority data of each node in a wireless network based on a southbound interface of an SDN controller, and obtaining the channel interference intensity, the spectrum occupancy rate and the service flow priority data of each node through a channel resource dynamic allocation table; generating a multi-dimensional resource view; according to the multi-dimensional resource view, multi-level coverage domains of the wireless network are divided, the service load level of each coverage domain is identified, and a pre-allocation scheme of cross-domain bandwidth resources is generated; and executing a pre-allocation scheme of cross-domain bandwidth resources by using a northbound interface of the SDN controller, and adjusting bandwidth allocation parameters of each coverage domain. According to the invention, visual monitoring, accurate division and flexible scheduling of the network resource state are realized, and the utilization efficiency of network bandwidth resources is remarkably improved.

The invention provides a communication method and a communication device. The method is used for indicating switching of a core network transmission path. The method specifically comprises the steps that the SMF or the PCF establishes a second transmission path, and the second transmission path comprises at least one transmission path between the terminal equipment and the core network equipment; and the SMF sends first request information to the UPF, and the first request information is used for indicating that the UPF starts the established second transmission path to transmit the next frame of message when the micro emergency situation exists in the current first transmission path by the user plane function network element. Through the method, the problem of transmission delay caused by core network path burst can be avoided under the scene that the media service flow generates micro burst, the data packet is prevented from arriving out of order, and the user experience is improved.

Disclosed in the present application are a service flow scheduling method, apparatus and device based on deep reinforcement learning, and a medium. The method comprises: acquiring target data, wherein the target data comprises a current target topology state, current target service flow information and current target link information of a time-sensitive network; and inputting the target data into a deep reinforcement learning model to obtain a scheduling scheme, so as to implement scheduling of service flows on the basis of the scheduling scheme, wherein the deep reinforcement learning model comprises an agent and an environment, the agent is configured to determine gate control orchestration of the scheduling scheme, and the environment is configured to determine slot orchestration of the scheduling scheme on the basis of the gate control orchestration.

The invention provides a communication method and system for a terminal and a cloud server, and the method comprises the steps: the terminal configures an agent client, sets an agent parameter at the agent client, starts an agent, and enters a first communication mode, and the agent parameter comprises a local agent port; in the first communication mode, the terminal applies for a service key from a cloud server, and if the service key is successfully acquired, the terminal is allowed to enter a cloud computer interface; wherein the service key is used for encrypting or decrypting a cloud resource service flow packet transmitted by the local agent port. A terminal proxy client is set to start a proxy, a secure communication mode between a terminal and a cloud server is entered, and a cloud resource service flow packet is encrypted by using service keys held at two ends, so that cloud resources are prevented from being intercepted, leaked and tampered in transmission, and office security is protected; encryption at a flow layer is realized through an agent, the execution efficiency is high, encryption and decryption are implemented by combining a symmetric cryptographic algorithm with a high encryption and decryption processing rate, so that the processing capability and the response speed of the whole system are extremely high, and non-inductive secure acquisition of cloud resources is realized; encryption is carried out on the flow layer, and compared with a service layer, keys can be saved; the terminal is set to obtain the service key and enter the cloud computer interface, so that unauthorized users or hostile attackers are prevented from operating the cloud computer, and the system security is improved.

The invention discloses a wireless ad hoc network routing and resource cross-layer joint optimization method based on a genetic algorithm. The method comprises the following steps: step 1, aiming at a plurality of end-to-end communication services in a wireless ad hoc network, carrying out mathematical modeling on a normalized difference sum of each service flow path hop count and a theoretical minimum value thereof and a constraint condition; performing joint optimization on link layer resource allocation and network layer routing decision; and step 2, solving the mathematical model based on a genetic algorithm to realize the targets of reasonable distribution of network resources and optimization of service quality. According to the method, link layer resource allocation and network layer routing decision are jointly optimized in a global mode under the condition that network communication resources are limited, it is ensured that a service flow is close to shortest path transmission as far as possible, end-to-end delay and network loads are reduced, and effective allocation of resources and flexible construction of routing are achieved.

The invention relates to the field of low-altitude communication network planning methods, in particular to a 5G three-dimensional coverage and capacity planning design method for low-altitude economy, which comprises the following steps: performing airspace range limitation and application scene division on a target airspace, establishing a mobile model of a low-altitude terminal, and providing dynamic input for simulation; the method comprises the following steps: establishing a dual-frequency heterogeneous network, and determining base station addresses covering targets at different heights and meeting different signal station spacing; performing three-dimensional coverage and quality simulation on the established dual-frequency heterogeneous network, performing network KPI evaluation on the simulation until the standard is reached, and outputting a network deployment planning scheme; deploying according to a network deployment planning scheme, predicting low-altitude service flow, and adjusting a beam direction and a PRB reservation ratio to realize on-demand allocation of resources; and carrying out actual measurement on the deployed network, collecting an air measurement index, comparing a comparison deviation between the air measurement index and a simulation result, and carrying out fine adjustment on the network according to the comparison deviation. According to the invention, diversified communication requirements are met, and the success rate of terminal access is improved.