Configuration method, system and network equipment of 5G network function

Abstract

The present invention relates to the field of communication network technology, and in particular to a configuration method, system and network equipment for 5G network functions. The method comprises the following steps: obtaining 5G network resource allocation data, integrating them, and obtaining 5G base station deployment data; analyzing the 5G base station deployment data to obtain a 5G network topology model; calculating the spectrum utilization rate of the 5G network topology model to obtain spectrum utilization rate data of base station coverage hotspot areas; optimizing frequency band allocation according to spectrum utilization rate data of base station coverage hotspot areas, thereby obtaining coverage area frequency band optimization data; optimizing base station radio frequency configuration of 5G base station deployment data to obtain base station radio frequency optimization data; optimizing hotspot area resource configuration of 5G network resource allocation data according to base station radio frequency optimization data and coverage area frequency band optimization data to obtain hotspot area resource optimization configuration data. The present invention can improve the resource utilization rate of 5G networks.

Description

Technical Field

[0001] The present invention relates to the field of communication network technology, and in particular to a configuration method, system and network equipment for 5G network functions. Background Art

[0002] With the development of mobile communication technology, 5G, as the fifth generation mobile communication technology standard, represents an important development direction of future communication networks. The application of 5G technology can not only support higher data transmission rates and lower latency, but also connect large-scale IoT devices, support high reliability and low power communication, and provide richer services and application scenarios. In 5G networks, how to effectively configure network functions is crucial. Network function configuration involves how to optimize and adjust the parameters and behaviors of each component in the network to achieve the best network performance, resource utilization efficiency and user experience. With the continuous advancement of technology and the continuous expansion of the network, traditional 5G network function configuration methods flexibly respond to these diverse service needs and performance requirements. Traditional configuration methods often rely on manual or automated configuration based on fixed rules, and these methods have a slow response speed. When the network load changes drastically or new service requirements emerge, the network configuration cannot be adjusted in time to cope with the changes, affecting user experience and network performance. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a 5G network function configuration method, system and network device to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for configuring 5G network functions includes the following steps:

[0005] Step S1: Acquire 5G network resource allocation data, and perform 5G base station deployment integration according to the 5G network resource allocation data, thereby obtaining 5G base station deployment data; perform network topology structure analysis according to the 5G base station deployment data, thereby obtaining a 5G network topology structure model;

[0006] Step S2: dividing the 5G network topology model into base station network coverage hotspot areas according to the 5G network resource allocation data, thereby obtaining base station network coverage hotspot area data, and performing spectrum utilization calculation on the base station network coverage hotspot area data, thereby obtaining base station coverage hotspot area spectrum utilization data;

[0007] Step S3: Performing coverage area network performance evaluation based on the spectrum utilization data of the base station coverage hotspot area, thereby obtaining coverage area network performance evaluation data; performing frequency band allocation optimization based on the coverage area network performance evaluation data, thereby obtaining coverage area frequency band optimization data;

[0008] Step S4: extracting 5G base station radio frequency features from the 5G base station deployment data to obtain 5G base station radio frequency data, and optimizing the base station radio frequency configuration of the 5G base station radio frequency data according to the spectrum utilization rate data of the base station coverage hotspot area to obtain base station radio frequency optimization data;

[0009] Step S5: Optimize the hotspot area resource configuration of the 5G network resource allocation data according to the base station radio frequency optimization data and the coverage area frequency band optimization data, so as to obtain the hotspot area resource optimization configuration data, and upload it to the 5G network communication management platform to perform the configuration optimization task.

[0010] The present invention can obtain 5G base station deployment data and network topology model by acquiring 5G network resource allocation data and performing base station deployment integration. These data and models provide a basis for subsequent steps, helping to understand the location and relationship of each base station in the network, as well as the overall structure of the network. It helps to optimize the physical layout and resource utilization of the network, ensuring that the coverage range and quality reach the optimal level. At the same time, effective base station deployment can reduce coverage dead spots and overlapping coverage, and improve network capacity and coverage effect. By analyzing the base station network topology model, dividing the coverage hotspot areas in the network, and calculating the spectrum utilization of these areas, it is helpful to identify areas with high load in the network and situations where the spectrum resource utilization efficiency is low. Based on these data, the power, antenna direction or frequency allocation of the base station can be adjusted to optimize coverage and capacity, thereby improving the performance and efficiency of the network. According to the spectrum utilization data of the base station coverage hotspot area, the network performance of the coverage area is evaluated, including indicators such as signal strength, transmission rate and delay, which can help determine whether it is necessary to reallocate the frequency band or adjust the coverage strategy to optimize network coverage and capacity. Through targeted optimization measures, the coverage quality and user experience of the network can be improved, especially in high-density user areas or weak signal areas. According to the spectrum utilization data of the base station coverage hotspot area, the RF configuration of each base station is optimized, including power control, antenna adjustment and frequency selection. Through precise RF configuration optimization, the coverage range and signal quality of the base station can be improved, interference and energy consumption can be reduced, and the reliability and efficiency of the network can be improved. According to the obtained base station RF optimization data and coverage area frequency band optimization data, the network resources are finally optimized and configured to ensure the optimal allocation of network resources in various hotspot areas, including spectrum resources, bandwidth and processing power. Through optimized configuration, efficient utilization of network resources can be achieved to meet the needs of different regions and service types, and improve overall network performance and user satisfaction. In summary, these steps work together at all levels of the 5G network, from physical deployment to RF optimization to resource configuration, with the aim of achieving refinement and optimization of network function configuration through data-driven methods to improve network performance, resource utilization efficiency and user experience.

[0011] Optionally, step S1 specifically includes:

[0012] Step S11: Acquire 5G network resource allocation data, and extract 5G base station identification features from the 5G network resource allocation data, thereby obtaining 5G base station identification data;

[0013] Step S12: extracting 5G base station resource allocation data from 5G network resource allocation data according to the 5G base station identification data, thereby obtaining 5G base station resource allocation data;

[0014] Step S13: performing 5G base station deployment integration on the 5G base station resource allocation data and the 5G base station identification data, thereby obtaining 5G base station deployment data;

[0015] Step S14: Perform network topology analysis on the 5G base station deployment data to obtain a 5G network topology model.

[0016] The present invention collects and obtains resource allocation data of each base station in a 5G network. These data include resources allocated to user equipment by different base stations in a specific time period, such as spectrum resources, bandwidth allocation, etc. By extracting the 5G base station identification features from these data, key identification information can be obtained for data processing and analysis in subsequent steps. By analyzing and understanding the resource allocation of different base stations, the utilization efficiency of resources in the 5G network can be optimized, and network performance and user experience can be improved. Obtaining real-time resource allocation data can help network operators or administrators to perform timely network management and adjustment to cope with different network loads and demand changes. Using the previously extracted base station identification data, the actual resource allocation data is extracted and sorted. These data can show the exact resource situation allocated to user equipment by different base stations in a specific time period, and can ensure the accuracy and completeness of the data, so that the analysis and decision-making in subsequent steps are based on the real resource allocation situation. Based on accurate resource allocation data, bottleneck problems in the network can be identified and solved, thereby improving the overall network performance. The data obtained in the first two steps are integrated and combined. The main purpose is to comprehensively consider resource allocation data and base station identification data to form complete 5G base station deployment data. These data can be used for further network planning and optimization. Taking into account resource allocation and base station identification data, a comprehensive understanding of the entire network can be formed, which helps to develop more effective deployment strategies and optimization plans. Provide data-based decision support, such as determining the deployment location of new base stations or adjusting the resource allocation of existing base stations. The integrated data is analyzed to establish a topological structure model of the 5G network. By analyzing the topological structure, potential problems in the network, such as bottlenecks or unnecessary overlapping coverage areas, can be discovered and resolved. Based on the topological structure model, future network expansion and upgrades can be predicted and planned to support the needs of more users and applications.

[0017] Optionally, step S14 is specifically:

[0018] Step S141: extracting 5G network node connection features according to 5G network resource allocation data, thereby obtaining 5G network node connection data;

[0019] Step S142: performing node connection statistics on the 5G network node connection data, thereby obtaining high-frequency connection node data and low-frequency node connection data;

[0020] Step S143: performing node association on the 5G base station deployment data according to the high-frequency connection node data and the low-frequency node connection data, thereby obtaining the high-frequency connection base station data and the low-frequency connection base station data;

[0021] Step S144: performing network connection topology analysis based on high-frequency connection base station data, thereby obtaining a relay base station network structure model; performing network connection topology analysis based on low-frequency connection base station data, thereby obtaining an edge base station network structure model;

[0022] Step S145: spatially merge the relay base station network structure model and the edge base station network structure model to obtain a 5G network topology model.

[0023] The present invention uses the previously acquired 5G network resource allocation data to extract node connection features. These features include the physical distance between base stations, signal transmission strength, frequency band utilization, etc. By extracting these features, connection relationship data between base stations can be established to form 5G network node connection data. Based on the node connection features, the connection relationship between base stations in the 5G network can be accurately established and described to form a network topology model. Understanding the node connection features helps to optimize signal transmission and coverage, and improve the coverage effect and transmission quality of the network. Statistical analysis is performed on the node connection data to identify high-frequency connection nodes and low-frequency connection nodes. High-frequency connection nodes refer to the connection relationship between base stations with higher connection frequencies, while low-frequency connection nodes are relatively few. By statistically analyzing high-frequency connection and low-frequency connection nodes, hot spots and low-load areas in the network can be identified and understood, thereby optimizing load balancing. According to the connection frequency distribution, the resource allocation strategy can be adjusted to improve the utilization efficiency of network resources and reduce resource waste. The node data of high-frequency connection and low-frequency connection are applied to the 5G base station deployment data to perform node association. This means mapping the known connection relationship to the actual base station deployment location to form high-frequency connection base station data and low-frequency connection base station data. Based on the actual connection data, the deployment of base stations is optimized and adjusted to support more stable and efficient network connections. Through node association, future network capacity planning can be carried out to ensure sufficient coverage and connectivity. Based on the high-frequency connection base station data and low-frequency connection base station data, a detailed analysis of the network connection topology is carried out. High-frequency connections reflect the network structure in the core area, while low-frequency connections involve the structure of edge areas or sparse connections. Through detailed topological structure analysis, key relay base stations and edge base stations can be accurately identified, and network optimization and improvement can be carried out in a targeted manner. Analyzing the topological structure can help predict potential problems and failure points in the network, and perform maintenance and repair in advance. The network structure model of the relay base station and the edge base station is merged in spatial structure. This means integrating the network topology of the core area and the edge area to form the final 5G network topology model. Through spatial structure merging, various parts of the entire 5G network can be comprehensively considered to form a comprehensive network perspective. During the merging process, the network structure and resource allocation can be continuously optimized to ensure the efficiency and performance of the overall network are in the best state.

[0024] Optionally, step S2 specifically includes:

[0025] Step S21: extracting base station signal power features and antenna pattern features from 5G base station deployment data, thereby obtaining base station signal power data and antenna pattern data;

[0026] Step S22: Calculate the base station coverage range according to the base station signal power data and the antenna pattern data, thereby obtaining the base station coverage range data;

[0027] Step S23: dividing the 5G network topology model into network hotspot areas according to the 5G network resource allocation data, thereby obtaining 5G network hotspot area data;

[0028] Step S24: spatially associate the base station coverage data and the 5G network hotspot area data to obtain the base station network coverage hotspot area data;

[0029] Step S25: Calculate the spectrum utilization of the base station network coverage hotspot area data according to the 5G network resource allocation data, so as to obtain the spectrum utilization data of the base station coverage hotspot area.

[0030] By measuring and analyzing the signal power transmitted by the base station, the present invention can understand the signal strength distribution of each base station at different locations. This is very important for evaluating coverage, signal strength and interference. The directivity of the antenna affects the effective range and signal quality of the base station coverage. By extracting the directional pattern characteristics of the antenna, the signal coverage in different directions can be accurately calculated, which helps to optimize network coverage and capacity. Based on the extracted power and directional pattern data, the actual coverage of each base station can be calculated. This is crucial for evaluating the quality of coverage, gap areas and signal attenuation, and helps to optimize the layout and configuration of base stations. Using 5G network resource allocation data, hot spots in the network are identified. These areas usually refer to user-intensive areas or high-traffic areas, which require special attention and optimization to improve user experience and network efficiency. Spatially correlating the coverage data of the base station with the 5G network hot spot area data can more accurately determine which areas need to enhance network coverage, thereby optimizing the allocation and utilization of network resources. Calculate the spectrum utilization rate of the base station coverage hot spot area. This helps to evaluate the efficiency of network resource utilization, optimize spectrum resource allocation, and ensure good service quality in high-traffic areas or hot spots.

[0031] Optionally, step S23 is specifically:

[0032] Step S231: Evaluate the base station space density of the 5G network topology model to obtain base station space density data;

[0033] Step S232: dividing the 5G network topology model into high base station density areas according to the base station spatial density data, thereby obtaining high base station density area data;

[0034] Step S233: Calculate the resource allocation ratio according to the 5G network resource allocation data, so as to obtain the resource allocation ratio data;

[0035] Step S234: clustering the 5G network resource allocation data into high-ratio resource allocation areas according to the resource allocation ratio data, thereby obtaining high-ratio resource allocation area data;

[0036] Step S235: Perform regional intersection calculation on the high base station density area data and the high ratio resource allocation area data to obtain 5G network hotspot area data.

[0037] The present invention can determine which areas have a higher base station density by evaluating the density of base stations in space. This is very important for understanding the coverage capability, capacity and signal quality distribution of the network. The base station spatial density data can reveal potential congested areas or areas with insufficient coverage in the network, providing basic data for further optimizing the network. Dividing the network into high base station density areas helps to accurately locate and manage areas covered by high-density base stations. These areas are urban centers, commercial areas or densely populated areas, requiring special network planning and optimization strategies to meet high traffic and high user needs. According to the network resource allocation data, the resource allocation ratio of different areas is calculated. This includes resources in terms of bandwidth, spectrum, processing power, etc. Through these data, the demand for resources in each area can be understood, which helps to optimize the allocation and utilization efficiency of resources. According to the resource allocation ratio data, the high-proportion resource allocation areas in the network are clustered. This can help identify specific areas with high resource demand and high performance requirements in the network. Cluster analysis can reveal areas with high resource utilization or concentrated demand, providing a basis for further resource optimization and network planning. By calculating the intersection of high base station density area data and high resource allocation ratio area data, we can determine the hot spots in the 5G network. These hot spots have both high base station density and high resource demand ratio, and are the key focus of network performance optimization. By concentrating resources to optimize these hot spots, we can effectively improve the overall network service quality and user experience.

[0038] Optionally, step S3 specifically includes:

[0039] Step S31: classifying the spectrum utilization rate based on the spectrum utilization rate data of the base station coverage hotspot area, thereby obtaining high spectrum utilization rate area data and low spectrum utilization rate area data;

[0040] Step S32: integrating spectrum utilization waveform characteristics according to spectrum utilization data of base station coverage hotspot areas, thereby obtaining spectrum utilization waveform characteristic data;

[0041] Step S33: performing regional spectrum waveform continuity statistics on the spectrum utilization rate waveform feature data, thereby obtaining high-continuity waveform spectrum regional data and low-continuity waveform spectrum regional data;

[0042] Step S34: performing a regional intersection operation on the high spectrum utilization area data and the high continuity waveform spectrum area data, so as to obtain high network performance coverage area data; performing a regional intersection operation on the low spectrum utilization area data and the low continuity waveform spectrum area data, so as to obtain low network performance coverage area data;

[0043] Step S35: performing regional spatial merging on the low network performance coverage area data and the high network performance coverage area data, thereby obtaining coverage area network performance evaluation data;

[0044] Step S36: Optimize frequency band allocation according to the coverage area network performance evaluation data, so as to obtain coverage area frequency band optimization data.

[0045] The present invention divides the area into two categories of high spectrum utilization and low spectrum utilization according to the spectrum utilization data of the base station coverage hotspot area. The purpose is to identify which areas have high or low spectrum resource utilization, and provide a basis for further spectrum optimization and resource allocation. The spectrum utilization data of the base station coverage hotspot area are integrated into spectrum utilization waveform feature data. These feature data can reflect the time-varying characteristics and fluctuations of spectrum utilization, help to understand the dynamic changes of spectrum use in the network, and provide detailed information for subsequent spectrum management and optimization. The spectrum utilization waveform feature data is subjected to continuity statistics to obtain high-continuity waveform spectrum areas and low-continuity waveform spectrum areas. Continuity statistics can help identify areas where spectrum utilization changes relatively smoothly or fluctuates greatly. This is crucial for determining the stability and reliability of spectrum resource allocation in the network. According to the intersection of high spectrum utilization area data and high-continuity waveform spectrum area data, high network performance coverage area data is obtained; at the same time, according to the intersection of low spectrum utilization area data and low-continuity waveform spectrum area data, low network performance coverage area data is obtained. These regional data help identify areas with excellent and undesirable spectrum utilization in the network, and provide goals and directions for local optimization of network performance. The data of low network performance coverage area is spatially merged with the data of high network performance coverage area to obtain comprehensive coverage area network performance evaluation data, which can guide further frequency band allocation and resource optimization strategies to improve the overall network coverage quality and user experience. Based on the coverage area network performance evaluation data, frequency band allocation is optimized. By reasonably allocating frequency band resources, the spectrum utilization and network performance of the coverage area can be effectively improved, thereby achieving better service coverage and user satisfaction.

[0046] Optionally, step S36 is specifically:

[0047] Step S361: classifying the performance evaluation areas according to the coverage area network performance evaluation data, thereby obtaining low network performance coverage area data and high network performance coverage area data;

[0048] Step S362: extracting spectrum utilization features from the low network performance coverage area data and the high network performance coverage area data respectively, thereby obtaining low network performance spectrum utilization data and high network performance spectrum utilization data;

[0049] Step S363: performing spectrum utilization distribution statistics on the low network performance spectrum utilization data and the high network performance spectrum utilization data, thereby obtaining frequency band utilization distribution data;

[0050] Step S364: Calculate the coverage difference of the low network performance coverage area data and the high network performance coverage area data, so as to obtain coverage area difference data;

[0051] Step S365: extracting regional frequency band allocation features from the 5G network resource allocation data, thereby obtaining regional frequency band allocation data;

[0052] Step S366: performing low-performance regional frequency band allocation compensation on the regional frequency band allocation data according to the frequency band utilization distribution data and the coverage area difference data, thereby obtaining coverage area frequency band optimization data.

[0053] The present invention divides the area into a low network performance coverage area and a high network performance coverage area according to the network performance evaluation data of the coverage area. This classification helps to identify problem areas in network coverage and performance, and provides goals and directions for further optimization. For the data of the low network performance coverage area and the high network performance coverage area, this step aims to extract the characteristics of spectrum utilization. Spectrum utilization is an important indicator for evaluating wireless network efficiency and resource utilization. By comparing the spectrum utilization characteristics of different regions, potential spectrum utilization efficiency problems or advantages can be revealed. Statistical analysis is performed on the low network performance spectrum utilization data and the high network performance spectrum utilization data. Through the distribution statistics of spectrum utilization, we can have a deeper understanding of the spectrum utilization in different regions, identify possible frequency band congestion or idleness, and provide a basis for optimizing and adjusting frequency band allocation. Calculate the coverage difference between the low network performance coverage area data and the high network performance coverage area data. By comparing these differences, the coverage quality differences between different regions can be quantitatively evaluated, so as to determine whether there is insufficient or excessive coverage, and provide guidance for optimizing coverage. For 5G network resource allocation data, the characteristics of regional frequency band allocation are extracted. These features include the utilization rate of the frequency band, allocation strategy, etc., which help analyze the current frequency band allocation status and the resource allocation differences between different regions. Based on the previously obtained frequency band utilization distribution data and coverage area difference data, the regional frequency band allocation is optimized and adjusted, especially to compensate for the frequency band allocation in low-performance areas. This process aims to improve the coverage and service quality in low-network performance areas by reallocating frequency band resources, thereby achieving the goal of optimizing overall network performance.

[0054] Optionally, step S4 is specifically:

[0055] Step S41: extracting 5G base station radio frequency features from 5G base station deployment data, thereby obtaining 5G base station radio frequency data;

[0056] Step S42: performing spectrum utilization distribution statistics on the spectrum utilization data of the base station coverage hotspot area, thereby obtaining base station frequency band utilization distribution data;

[0057] Step S43: performing congestion evaluation on the base station frequency band utilization distribution data, thereby obtaining frequency band congestion data;

[0058] Step S44: Optimizing radio frequency parameters of 5G base station radio frequency data according to the frequency band congestion data, thereby obtaining an optimized radio frequency parameter group;

[0059] Step S45: performing radio frequency simulation on the optimized radio frequency parameter group, thereby obtaining optimized radio frequency parameter simulation data;

[0060] Step S46: selecting an energy efficiency optimization parameter group for the optimized radio frequency parameter simulation data, thereby obtaining base station radio frequency optimization data.

[0061] The present invention collects and extracts the radio frequency characteristic data of 5G base stations. By analyzing these data, key information such as the radio frequency signal quality, transmission power, and frequency usage of the base station can be understood. These data are crucial for subsequent optimization steps because they provide a basic reference for the current operating status of the base station. Analyze the spectrum utilization of the base station in the coverage hotspot area. By statistically analyzing the distribution data of the spectrum utilization, the utilization of different frequency bands can be determined, and then the load and utilization efficiency of the base station in each frequency band can be evaluated. This data is very important for optimizing the allocation of base station resources and avoiding frequency band congestion. Based on the data of the first two steps, the congestion degree of the utilization of each frequency band of the base station is evaluated. This evaluation can help determine which frequency bands may have congestion problems, so as to take timely measures to optimize, such as adjusting frequency band allocation or increasing resources. Using the frequency band congestion data obtained above, the radio frequency parameters of the 5G base station are optimized and adjusted. This may include adjusting the transmission power, frequency selection, antenna direction, etc., aiming to maximize the efficiency of frequency band utilization while avoiding or reducing congestion. Through radio frequency simulation, the performance of the optimized radio frequency parameters in the actual environment can be simulated. These simulation data can help verify and adjust the previously optimized parameter combinations to ensure that the expected results can be achieved in actual deployment. Select the parameter combination with the best energy efficiency based on the RF simulation data. By comprehensively considering factors such as spectrum utilization, congestion, and coverage, determine the optimal RF parameter configuration to achieve the best performance under existing resources.

[0062] Optionally, the present invention further provides a 5G network function configuration system, which is used to execute the 5G network function configuration method as described above, and the 5G network function configuration system includes:

[0063] A topology analysis module is used to obtain 5G network resource allocation data, and perform 5G base station deployment integration based on the 5G network resource allocation data, thereby obtaining 5G base station deployment data; perform network topology analysis based on the 5G base station deployment data, thereby obtaining a 5G network topology model;

[0064] A coverage hotspot area division module is used to divide the base station network coverage hotspot area of ​​the 5G network topology model according to the 5G network resource allocation data, thereby obtaining the base station network coverage hotspot area data, and to calculate the spectrum utilization rate of the base station network coverage hotspot area data, thereby obtaining the spectrum utilization rate data of the base station coverage hotspot area;

[0065] The frequency band allocation optimization module is used to evaluate the network performance of the coverage area according to the spectrum utilization data of the base station coverage hotspot area, so as to obtain the network performance evaluation data of the coverage area; optimize the frequency band allocation according to the network performance evaluation data of the coverage area, so as to obtain the frequency band optimization data of the coverage area;

[0066] The base station radio frequency configuration optimization module is used to extract 5G base station radio frequency features from 5G base station deployment data to obtain 5G base station radio frequency data, and optimize the base station radio frequency configuration of the 5G base station radio frequency data based on the spectrum utilization rate data of the base station coverage hotspot area to obtain base station radio frequency optimization data;

[0067] The regional resource configuration optimization module is used to optimize the hotspot area resource configuration of the 5G network resource allocation data according to the base station radio frequency optimization data and the coverage area frequency band optimization data, so as to obtain the hotspot area resource optimization configuration data and upload it to the 5G network communication management platform to perform the configuration optimization task.

[0068] The 5G network function configuration system of the present invention can implement any 5G network function configuration method of the present invention, and is used to combine the operation and signal transmission medium between each module to complete the 5G network function configuration method. The internal modules of the system cooperate with each other to improve the utilization rate of network resources.

[0069] Optionally, the present invention also provides a network device, including a network device main body, a power supply unit and an electrical control unit, the power supply unit is installed inside the network device main body, the electrical control unit is electrically connected to the power supply unit, the electrical control unit is used to charge and control the network device main body, and the electrical control unit is used to execute the configuration method of the 5G network function as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0071] Figure 1 A schematic diagram of the steps of the configuration method of the 5G network function of the present invention;

[0072] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0073] Figure 3 Detailed step flow diagram of step S2 in the present invention;

[0074] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0075] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0076] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0077] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0078] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for configuring a 5G network function, the method comprising the following steps:

[0079] Step S1: Acquire 5G network resource allocation data, and perform 5G base station deployment integration according to the 5G network resource allocation data, thereby obtaining 5G base station deployment data; perform network topology structure analysis according to the 5G base station deployment data, thereby obtaining a 5G network topology structure model;

[0080] In this embodiment, obtaining 5G network resource allocation data involves collecting spectrum allocation, bandwidth allocation and network topology information in various regions. For example, by cooperating with telecom operators, the frequency band usage and base station deployment in different cities can be obtained. Based on these data, 5G base station deployment integration can be carried out to ensure the rationality of the base station location and the optimization of coverage. For example, GIS technology is used to analyze the geographical location and coverage radius of each base station to maximize the coverage effect and avoid spectrum overlap. Then, graph theory technology is used to perform topological structure analysis based on the deployment of base stations and the connection relationship of network nodes to obtain a 5G network topology model.

[0081] Step S2: dividing the 5G network topology model into base station network coverage hotspot areas according to the 5G network resource allocation data, thereby obtaining base station network coverage hotspot area data, and performing spectrum utilization calculation on the base station network coverage hotspot area data, thereby obtaining base station coverage hotspot area spectrum utilization data;

[0082] In this embodiment, the base station network coverage hotspot area is divided according to the 5G network topology model. This includes identifying densely populated areas and high-traffic areas in the city to accurately divide the coverage hotspot areas. For example, more dense base stations are deployed in the city center and commercial areas to meet the needs of high-traffic and high-density users. At the same time, the spectrum utilization rate of the base station network coverage hotspot area data is calculated to ensure the effective use of spectrum resources and avoid congestion and interference.

[0083] Step S3: Performing coverage area network performance evaluation based on the spectrum utilization data of the base station coverage hotspot area, thereby obtaining coverage area network performance evaluation data; performing frequency band allocation optimization based on the coverage area network performance evaluation data, thereby obtaining coverage area frequency band optimization data;

[0084] In this embodiment, the network is optimized and adjusted using the coverage area network performance evaluation data. For example, the signal coverage and data transmission speed of the base station are evaluated through real-time data monitoring and analysis to improve the stability and performance of the network. Frequency band allocation optimization ensures that the interference between different frequency bands is minimized and optimizes the balance between network capacity and coverage. For example, by simulating different frequency band configuration schemes, the coverage effect and signal interference of each scheme are evaluated, and the optimal frequency band allocation strategy is selected.

[0085] Step S4: extracting 5G base station radio frequency features from the 5G base station deployment data to obtain 5G base station radio frequency data, and optimizing the base station radio frequency configuration of the 5G base station radio frequency data according to the spectrum utilization rate data of the base station coverage hotspot area to obtain base station radio frequency optimization data;

[0086] In this embodiment, RF features such as signal coverage, power distribution, and signal-to-noise ratio are extracted from 5G base station deployment data. Based on the spectrum utilization data of base station coverage hotspots, the RF configuration is optimized to improve signal coverage quality and network capacity utilization. For example, the base station antenna direction and power output are adjusted, and the RF parameters of each base station are optimized through automated tool monitoring and adjustment to adapt to real-time changes in network load and signal demand.

[0087] Step S5: Optimize the hotspot area resource configuration of the 5G network resource allocation data according to the base station radio frequency optimization data and the coverage area frequency band optimization data, so as to obtain the hotspot area resource optimization configuration data, and upload it to the 5G network communication management platform to perform the configuration optimization task.

[0088] In this embodiment, the hotspot area resource configuration is optimized based on the base station radio frequency optimization and coverage area frequency band optimization data. This includes dynamically adjusting the resource allocation of each base station to adapt to real-time network traffic and user demand changes. For example, through intelligent algorithms and machine learning models, the frequency band allocation and resource utilization of base stations are optimized in real time to ensure that the network can remain stable and efficient during high-load periods. Finally, the optimized configuration data is uploaded to the 5G network communication management platform to perform automated configuration tasks to achieve continuous optimization and improvement of the network.

[0089] Optionally, step S1 specifically includes:

[0090] Step S11: Acquire 5G network resource allocation data, and extract 5G base station identification features from the 5G network resource allocation data, thereby obtaining 5G base station identification data;

[0091] In this embodiment, obtaining 5G network resource allocation data involves collecting various information about base station resource allocation from the telecom operator's 5G network management system, such as spectrum allocation, bandwidth utilization, and user connection status. These data are usually transmitted in the form of data streams or data packets and need to be extracted from network devices through appropriate interfaces and protocols (such as RESTful API or SNMP protocol). Once these data are obtained, the next task is to extract 5G base station identification features. This involves preprocessing and analyzing the data to identify and extract unique identifiers for each 5G base station, such as physical site IDs or logical identifiers. For example, data analysis techniques (such as data mining algorithms or machine learning models) can be used to automatically identify and extract these identifiers to ensure accuracy and completeness.

[0092] Step S12: extracting 5G base station resource allocation data from 5G network resource allocation data according to the 5G base station identification data, thereby obtaining 5G base station resource allocation data;

[0093] In this embodiment, the original network resource allocation data can be further processed based on the extracted 5G base station identification data to obtain more detailed 5G base station resource allocation data. This includes extracting specific resource usage from the identified base stations, such as frequency band allocation, channel utilization, and transmission power. Custom scripts can be written or professional data processing software can be used to extract and organize the required resource allocation information from a large amount of raw data.

[0094] Step S13: performing 5G base station deployment integration on the 5G base station resource allocation data and the 5G base station identification data, thereby obtaining 5G base station deployment data;

[0095] In this embodiment, the 5G base station resource allocation data and identification data are integrated and analyzed. This step usually requires integrating data from different sources and ensuring the consistency and accuracy of the data. For example, a database management system (such as MySQL or MongoDB) can be used to store and manage this data, and query and analysis scripts can be written to understand and summarize the base station resource allocation. This integration not only helps to optimize resource utilization, but also provides basic data support for subsequent network planning and optimization. The base station spectrum allocation characteristics contained in the 5G base station resource allocation data are combined with the identification data of each base station to form a complete 5G base station deployment data set. This makes the specific deployment of each base station in the network clearly visible by associating the location information, resource allocation information and spectrum usage of each base station.

[0096] Step S14: Perform network topology analysis on the 5G base station deployment data to obtain a 5G network topology model.

[0097] In this embodiment, by performing network topology analysis on the integrated 5G base station deployment data, a topology model of the 5G network can be established. This includes analyzing key parameters such as the connection mode, transmission path, data flow and delay between base stations. Network modeling tools such as MATLAB or professional network simulation software can be used for real-time data collection and analysis. Through these analyses, the network layout and configuration can be optimized to meet the network performance requirements of different regions and user needs.

[0098] Optionally, step S14 is specifically:

[0099] Step S141: extracting 5G network node connection features according to 5G network resource allocation data, thereby obtaining 5G network node connection data;

[0100] In this embodiment, the 5G network node connection feature extraction is performed based on the 5G network resource allocation data to obtain the 5G network node connection data. The resource allocation information reported by each 5G base station can be used, such as frequency band utilization, bandwidth allocation, and connection duration. Through these data, the connection characteristics of each 5G network node can be identified, including its role in the network (such as core node, edge node), the type of connected device (such as mobile phone, IoT device), and connection quality (such as delay, packet loss rate) and other information. For example, for a 5G base station, its importance and load in the network topology can be judged by analyzing its frequency band utilization and device connection duration. If a base station frequently connects a large number of devices and has a high frequency band utilization, it can be shown that it plays the role of a core node in the network.

[0101] Step S142: performing node connection statistics on the 5G network node connection data, thereby obtaining high-frequency connection node data and low-frequency node connection data;

[0102] In this embodiment, node connection statistics are performed on the 5G network node connection data to obtain high-frequency connection node data and low-frequency node connection data. By performing statistical analysis on the connection data of all nodes in the 5G network, it can be found which nodes are frequently connected and which nodes are rarely connected. For example, through statistical analysis, it can be found that some 5G base stations maintain high-frequency connections with a large number of user devices, and these base stations may be located in densely populated areas or commercial areas. Low-frequency node connection data may correspond to remote areas or areas with less connection demand.

[0103] Step S143: performing node association on the 5G base station deployment data according to the high-frequency connection node data and the low-frequency node connection data, thereby obtaining the high-frequency connection base station data and the low-frequency connection base station data;

[0104] In this embodiment, the 5G base station deployment data is node-associated according to the high-frequency connection node data and the low-frequency node connection data, thereby obtaining high-frequency connection base station data and low-frequency connection base station data. This involves associating the obtained high-frequency and low-frequency connection node data with the deployment locations of the actual 5G base stations to determine which base stations are suitable as high-frequency connection nodes and which are suitable as low-frequency connection nodes. For example, high-frequency connection base stations require more bandwidth resources and network capacity support, so they can be considered for deployment in densely populated areas or near transportation hubs. Low-frequency connection base stations can be given priority for deployment in remote areas or sparsely populated areas to provide basic network coverage.

[0105] Step S144: performing network connection topology analysis based on high-frequency connection base station data, thereby obtaining a relay base station network structure model; performing network connection topology analysis based on low-frequency connection base station data, thereby obtaining an edge base station network structure model;

[0106] In this embodiment, a network connection topology structure analysis is performed based on high-frequency connection base station data to obtain a relay base station network structure model; and a network connection topology structure analysis is performed based on low-frequency connection base station data to obtain an edge base station network structure model. In this step, network connection topology analysis is performed for high-frequency connection base station data and low-frequency connection base station data, respectively, to establish network structure models for different types of base stations. For example, for high-frequency connection base stations, it is necessary to consider their relay role in the network, analyze their direct connection relationship and transmission path with surrounding base stations through graph theory methods, and establish the core structure of the network. For low-frequency connection base stations, the network structure model may focus more on the distribution characteristics of edge deployment and its connection method with core nodes.

[0107] Step S145: spatially merge the relay base station network structure model and the edge base station network structure model to obtain a 5G network topology model.

[0108] In this embodiment, the spatial structures of the relay base station network structure model and the edge base station network structure model are merged to obtain a 5G network topology model. Finally, the obtained relay base station network structure model and edge base station network structure model are merged and optimized in spatial structure to form a complete 5G network topology model. For example, by merging the network structures of the relay base station and the edge base station, it can be ensured that the entire 5G network is effectively optimized and balanced in terms of coverage and connection quality. This process involves comprehensive considerations such as base station deployment adjustment, signal coverage analysis, and network resource allocation strategy to ensure that the final network topology can achieve efficient, stable and comprehensive coverage.

[0109] Optionally, step S2 specifically includes:

[0110] Step S21: extracting base station signal power features and antenna pattern features from 5G base station deployment data, thereby obtaining base station signal power data and antenna pattern data;

[0111] In this embodiment, the key step is to extract the base station signal power characteristics and antenna pattern characteristics of the 5G base station deployment data. The base station signal power data can be obtained through measurement and simulation, covering different frequency bands and power levels. The antenna pattern data describes the radiation characteristics of each base station antenna in space, including the main lobe direction, beam width, etc. For example, through quantitative measurement and simulation, the signal power distribution and radiation pattern of each base station in different directions and frequency bands can be obtained, thereby providing the necessary data basis for subsequent coverage calculations.

[0112] Step S22: Calculate the base station coverage range according to the base station signal power data and the antenna pattern data, thereby obtaining the base station coverage range data;

[0113] In this embodiment, the base station coverage range is calculated based on the obtained base station signal power data and antenna pattern data. This process uses a wireless propagation model (such as a Free Space Path Loss model or an Okumura-Hata model) combined with actual measurement data to calculate the coverage range of each base station, that is, the geographical area that can be covered. For example, by analyzing factors such as the base station's transmit power, antenna gain, and environmental attenuation, the effective coverage area of ​​each base station under specific geographical conditions can be accurately estimated, providing a basis for subsequent network planning and optimization.

[0114] Step S23: dividing the 5G network topology model into network hotspot areas according to the 5G network resource allocation data, thereby obtaining 5G network hotspot area data;

[0115] In this embodiment, the 5G network topology model is divided into network hotspot areas according to the 5G network resource allocation data. This uses network traffic analysis and user data demand prediction to determine high-load areas and hotspot areas in the network. For example, by analyzing the data traffic of a big data center, the connection mode of user equipment, and the service type, hotspot areas in the network that require additional network resource support, such as commercial centers, residential areas, etc., can be identified.

[0116] Step S24: spatially associate the base station coverage data and the 5G network hotspot area data to obtain the base station network coverage hotspot area data;

[0117] In this embodiment, spatial correlation analysis is performed based on the obtained base station coverage data and 5G network hotspot area data. This compares and analyzes the actual coverage of the base station with the high-load area of ​​the network to determine which base stations cover important hotspot areas. For example, the base station coverage layer can be overlaid and analyzed with the hotspot area map through a geographic information system (GIS) tool to accurately determine the coverage and influence range of each base station in the network hotspot area.

[0118] Step S25: Calculate the spectrum utilization of the base station network coverage hotspot area data according to the 5G network resource allocation data, so as to obtain the spectrum utilization data of the base station coverage hotspot area.

[0119] In this embodiment, spectrum utilization is calculated for base station network coverage hotspot area data based on 5G network resource allocation data. The spectrum utilization of network hotspot areas can be evaluated by analyzing the usage and demand of each base station on spectrum resources. For example, through spectrum scanners and wireless network analysis tools, the spectrum occupancy of each base station in a specific time period can be monitored and recorded to calculate spectrum utilization, thereby optimizing network resource allocation and spectrum management strategies to ensure efficient use of available spectrum resources.

[0120] Optionally, step S23 is specifically:

[0121] Step S231: Evaluate the base station space density of the 5G network topology model to obtain base station space density data;

[0122] In this embodiment, when evaluating the spatial density of base stations, it is first necessary to consider the topological structure model of the 5G network, which includes the distribution and density of base stations. Through spatial analysis and mathematical modeling, the density of base stations around each base station can be evaluated, that is, the statistical characteristics of the number of base stations per unit area or volume. For example, using geographic information system (GIS) tools and spatial statistical methods, the spatial distribution density of base stations in each area can be calculated, which helps to determine which areas have high-density base station deployment.

[0123] Step S232: dividing the 5G network topology model into high base station density areas according to the base station spatial density data, thereby obtaining high base station density area data;

[0124] In this embodiment, based on the base station spatial density data obtained in step S231, the 5G network topology model is divided into high base station density areas. This uses a spatial clustering algorithm (such as DBSCAN or K-means) to divide and identify areas with high base station density. For example, through clustering analysis and hotspot detection algorithms, hotspot areas in cities can be identified. These areas usually have higher density base station coverage and require additional network resource support.

[0125] Step S233: Calculate the resource allocation ratio according to the 5G network resource allocation data, so as to obtain the resource allocation ratio data;

[0126] In this embodiment, the resource allocation ratio is calculated based on the 5G network resource allocation data. This involves analyzing the data traffic, user demand, and service level agreement (SLA) in different areas of the network to determine the demand ratio of network resources (such as spectrum and bandwidth) in each area. For example, through traffic measurement and user behavior analysis, it can be determined which areas need more resource support, thereby optimizing the network resource allocation strategy.

[0127] Step S234: clustering the 5G network resource allocation data into high-ratio resource allocation areas according to the resource allocation ratio data, thereby obtaining high-ratio resource allocation area data;

[0128] In this embodiment, based on the resource allocation ratio data, the 5G network resource allocation data is clustered into high-ratio resource allocation areas. This uses a clustering algorithm to aggregate and identify areas with high resource demand ratios. For example, through cluster analysis and data mining techniques, high-traffic areas or high-service demand areas can be identified, which need to give priority to resource allocation and network optimization.

[0129] Step S235: Perform regional intersection calculation on the high base station density area data and the high ratio resource allocation area data to obtain 5G network hotspot area data.

[0130] In this embodiment, the regional intersection calculation is performed on the data of high base station density areas and high-ratio resource allocation area data to obtain the 5G network hotspot area data. This step uses spatial analysis and geographic information system technology to overlap the high-density base station coverage area with the high resource demand area to identify the hotspot areas in the network that have both high base station density and high resource demand. For example, through map overlay and spatial intersection analysis, it is possible to determine the network hotspot areas that need to be focused on and optimized to support high-quality services and user experience.

[0131] Optionally, step S3 specifically includes:

[0132] Step S31: classifying the spectrum utilization rate based on the spectrum utilization rate data of the base station coverage hotspot area, thereby obtaining high spectrum utilization rate area data and low spectrum utilization rate area data;

[0133] In this embodiment, when the spectrum utilization data of the base station coverage hotspot area is classified, a data clustering or threshold division method can be used. For example, the spectrum utilization can be divided into a high spectrum utilization area according to the area where it is higher than a preset threshold, and the area where it is lower than the threshold is divided into a low spectrum utilization area. For example, when the spectrum utilization exceeds 70%, it is divided into a high spectrum utilization area; when it is lower than 30%, it is divided into a low spectrum utilization area.

[0134] Step S32: integrating spectrum utilization waveform characteristics according to spectrum utilization data of base station coverage hotspot areas, thereby obtaining spectrum utilization waveform characteristic data;

[0135] In this embodiment, when integrating spectrum utilization waveform features based on spectrum utilization data of base station coverage hotspot areas, it is possible to extract statistical features such as the mean, variance, kurtosis, and skewness of the spectrum utilization waveforms of each area, and then integrate these statistical features together. For example, for high spectrum utilization areas, the mean and variance of the waveform can be extracted as features; for low spectrum utilization areas, the kurtosis and skewness of the waveform are focused on.

[0136] Step S33: performing regional spectrum waveform continuity statistics on the spectrum utilization rate waveform feature data, thereby obtaining high-continuity waveform spectrum regional data and low-continuity waveform spectrum regional data;

[0137] In this embodiment, when performing regional spectrum waveform continuity statistics on spectrum utilization waveform feature data, the time domain and frequency domain information of the waveform can be used for analysis. For example, the autocorrelation function of the waveform or the frequency distribution characteristics in the spectrum diagram can be calculated. For high-continuity waveform spectrum regions, a relatively stable frequency distribution and waveform shape are exhibited; while low-continuity waveform spectrum regions have large frequency changes or irregular waveform shapes.

[0138] Step S34: performing a regional intersection operation on the high spectrum utilization area data and the high continuity waveform spectrum area data, so as to obtain high network performance coverage area data; performing a regional intersection operation on the low spectrum utilization area data and the low continuity waveform spectrum area data, so as to obtain low network performance coverage area data;

[0139] In this embodiment, when performing a regional intersection operation on the high spectrum utilization area data and the high continuity waveform spectrum area data, an area with high network performance coverage can be determined. For example, the overlapping parts of the high spectrum utilization area and the high continuity waveform spectrum area are regarded as coverage areas with high network performance, and these areas are suitable for allocation to high-demand or high-density user groups. The overlapping parts of the low spectrum utilization area and the low continuity waveform spectrum area are regarded as coverage areas with low network performance, and these areas require certain network communication adjustments.

[0140] Step S35: performing regional spatial merging on the low network performance coverage area data and the high network performance coverage area data, thereby obtaining coverage area network performance evaluation data;

[0141] In this embodiment, when the low network performance coverage area data and the high network performance coverage area data are spatially merged, they can be merged based on spatial proximity or coverage range. For example, spatially adjacent areas with different coverage performance are merged into a larger coverage area, thereby comprehensively considering the balanced distribution of network performance.

[0142] Step S36: Optimize frequency band allocation according to the coverage area network performance evaluation data, so as to obtain coverage area frequency band optimization data.

[0143] In this embodiment, when optimizing frequency band allocation based on coverage area network performance evaluation data, a dynamic spectrum allocation strategy or intelligent frequency band management method may be used. For example, according to network load conditions and user needs in different areas, the allocation ratio or priority of frequency bands may be adjusted to improve overall network efficiency and service quality.

[0144] Optionally, step S36 is specifically:

[0145] Step S361: classifying the performance evaluation areas according to the coverage area network performance evaluation data, thereby obtaining low network performance coverage area data and high network performance coverage area data;

[0146] In this embodiment, when classifying the performance evaluation area of ​​the coverage area network performance evaluation data, the area can be classified based on the collected signal strength, signal-to-noise ratio, data transmission rate and other indicators. For example, the collected field strength data is used to divide the coverage area into a high network performance coverage area with high signal strength and a low network performance coverage area with low signal strength. In this way, it is possible to accurately determine which areas need to be further optimized or adjusted in network resource allocation. The coverage area network performance evaluation data can also be classified according to the performance evaluation areas defined in advance.

[0147] Step S362: extracting spectrum utilization features from the low network performance coverage area data and the high network performance coverage area data respectively, thereby obtaining low network performance spectrum utilization data and high network performance spectrum utilization data;

[0148] In this embodiment, when extracting spectrum utilization features from low network performance coverage area data and high network performance coverage area data, spectrum utilization data of different areas can be analyzed. For example, for low network performance areas, features such as the average value, variance, and frequency distribution of spectrum utilization can be extracted; for high network performance areas, features such as the volatility and peak utilization of spectrum utilization can be focused on. These features can help evaluate the spectrum utilization efficiency and performance of the area.

[0149] Step S363: performing spectrum utilization distribution statistics on the low network performance spectrum utilization data and the high network performance spectrum utilization data, thereby obtaining frequency band utilization distribution data;

[0150] In this embodiment, when performing spectrum utilization distribution statistics on low network performance spectrum utilization data and high network performance spectrum utilization data, methods such as histograms or density estimation can be used. For example, a spectrum utilization distribution map can be drawn to analyze the distribution of different spectrum utilizations in the frequency bands of the entire network. These statistical data are helpful for understanding the allocation of spectrum resources and the spectrum utilization characteristics of different regions.

[0151] Step S364: Calculate the coverage difference of the low network performance coverage area data and the high network performance coverage area data, so as to obtain coverage area difference data;

[0152] In this embodiment, when calculating the coverage difference between the low network performance coverage area data and the high network performance coverage area data, a signal transmission model and a coverage analysis tool may be used. For example, based on the collected coverage data and the wireless signal strength model, the coverage overlap or coverage difference between different areas is calculated, thereby quantifying the coverage quality and difference of different areas.

[0153] Step S365: extracting regional frequency band allocation features from the 5G network resource allocation data, thereby obtaining regional frequency band allocation data;

[0154] In this embodiment, when extracting regional frequency band allocation features from 5G network resource allocation data, it can be based on the frequency band resource management strategy and dynamic spectrum allocation technology of the 5G network. For example, the number of frequency bands allocated to each region, the frequency band bandwidth, the frequency band usage and other features are extracted. These features reflect the frequency band resource utilization efficiency and allocation balance of different regions.

[0155] Step S366: performing low-performance regional frequency band allocation compensation on the regional frequency band allocation data according to the frequency band utilization distribution data and the coverage area difference data, thereby obtaining coverage area frequency band optimization data.

[0156] In this embodiment, when the regional frequency band allocation data is used to compensate the frequency band allocation of the low-performance area according to the frequency band utilization distribution data and the coverage area difference data, a dynamic spectrum sharing technology or a frequency band reallocation algorithm can be used. For example, according to the frequency band utilization distribution and coverage difference of the low-performance area, the frequency band allocation strategy is adjusted or additional frequency band resources are added to improve the coverage quality and network performance of the low-performance area.

[0157] Optionally, step S4 is specifically:

[0158] Step S41: extracting 5G base station radio frequency features from 5G base station deployment data, thereby obtaining 5G base station radio frequency data;

[0159] In this embodiment, RF features are extracted from 5G base station deployment data to ensure the effective use of spectrum resources and optimization of network performance for each base station. For example, RF parameters such as antenna configuration, operating frequency band, transmit power, antenna height, etc. of each base station can be collected. These data can be obtained through on-site measurements or network planning tools to ensure that the RF characteristics of each base station are accurately recorded and analyzed.

[0160] Step S42: performing spectrum utilization distribution statistics on the spectrum utilization data of the base station coverage hotspot area, thereby obtaining base station frequency band utilization distribution data;

[0161] In this embodiment, it is key to perform spectrum utilization distribution statistics for spectrum utilization data in base station coverage hotspot areas. This includes analyzing the spectrum utilization of each base station in different frequency bands, such as the spectrum occupancy ratio during high-load periods and low-load periods. Through statistical analysis, base station frequency band utilization distribution data can be obtained to help determine which frequency bands have over-use of spectrum resources or potential bottleneck problems.

[0162] Step S43: performing congestion evaluation on the base station frequency band utilization distribution data, thereby obtaining frequency band congestion data;

[0163] In this embodiment, the congestion degree of the base station frequency band utilization distribution data is evaluated. The goal of this step is to quantify the congestion of each frequency band, which is usually completed by calculating the ratio between the utilization rate of each frequency band and its capacity. For example, for a frequency band with a frequency band utilization rate higher than 80%, it indicates that there is a serious congestion problem, and the radio frequency parameters need to be optimized to share the load or increase the frequency band capacity.

[0164] Step S44: Optimizing radio frequency parameters of 5G base station radio frequency data according to the frequency band congestion data, thereby obtaining an optimized radio frequency parameter group;

[0165] In this embodiment, it is necessary to optimize the RF parameters of the 5G base station RF data according to the congestion data. This involves adjusting the base station's transmit power, antenna pattern, frequency band switching strategy, etc. to optimize network capacity and coverage. For example, the RF parameters of the base station are adjusted through dynamic power control or intelligent frequency band allocation algorithms to ensure that the network maintains good performance during both high-load and low-load periods.

[0166] Step S45: performing radio frequency simulation on the optimized radio frequency parameter group, thereby obtaining optimized radio frequency parameter simulation data;

[0167] In this embodiment, RF simulation is performed on the optimized RF parameter group to verify the effect of parameter optimization. This can be achieved through RF simulation software or simulators to evaluate the actual impact of parameter optimization on network performance, coverage, and frequency band utilization. For example, network coverage and user experience under different RF parameter configurations are simulated to confirm the effectiveness and feasibility of the optimization solution.

[0168] Step S46: selecting an energy efficiency optimization parameter group for the optimized radio frequency parameter simulation data, thereby obtaining base station radio frequency optimization data.

[0169] In this embodiment, the energy efficiency optimization parameter group is selected based on the RF simulation data. This includes evaluating the performance of various optimization schemes in terms of energy efficiency, such as the utilization efficiency of unit spectrum resources or the energy consumption ratio. By selecting the RF parameter combination with the best energy efficiency, it is possible to effectively control energy consumption and operating costs while improving network performance, and achieve the best results of base station RF optimization.

[0170] Optionally, the present invention further provides a 5G network function configuration system, which is used to execute the 5G network function configuration method as described above, and the 5G network function configuration system includes:

[0171] A topology analysis module is used to obtain 5G network resource allocation data, and perform 5G base station deployment integration based on the 5G network resource allocation data, thereby obtaining 5G base station deployment data; perform network topology analysis based on the 5G base station deployment data, thereby obtaining a 5G network topology model;

[0172] A coverage hotspot area division module is used to divide the base station network coverage hotspot area of ​​the 5G network topology model according to the 5G network resource allocation data, thereby obtaining the base station network coverage hotspot area data, and to calculate the spectrum utilization rate of the base station network coverage hotspot area data, thereby obtaining the spectrum utilization rate data of the base station coverage hotspot area;

[0173] The frequency band allocation optimization module is used to evaluate the network performance of the coverage area according to the spectrum utilization data of the base station coverage hotspot area, so as to obtain the network performance evaluation data of the coverage area; optimize the frequency band allocation according to the network performance evaluation data of the coverage area, so as to obtain the frequency band optimization data of the coverage area;

[0174] The base station radio frequency configuration optimization module is used to extract 5G base station radio frequency features from 5G base station deployment data to obtain 5G base station radio frequency data, and optimize the base station radio frequency configuration of the 5G base station radio frequency data based on the spectrum utilization rate data of the base station coverage hotspot area to obtain base station radio frequency optimization data;

[0175] The regional resource configuration optimization module is used to optimize the hotspot area resource configuration of the 5G network resource allocation data according to the base station radio frequency optimization data and the coverage area frequency band optimization data, so as to obtain the hotspot area resource optimization configuration data and upload it to the 5G network communication management platform to perform the configuration optimization task.

[0176] The 5G network function configuration system of the present invention can implement any 5G network function configuration method of the present invention, and is used to combine the operation and signal transmission medium between each module to complete the 5G network function configuration method. The internal modules of the system cooperate with each other to improve the utilization rate of network resources.

[0177] Optionally, the present invention also provides a network device, including a network device main body, a power supply unit and an electrical control unit, the power supply unit is installed inside the network device main body, the electrical control unit is electrically connected to the power supply unit, the electrical control unit is used to charge and control the network device main body, and the electrical control unit is used to execute the configuration method of the 5G network function as described above.

[0178] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0179] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for configuring a 5G network function, characterized in that: The following steps are involved: Step S1: Acquire 5G network resource allocation data, and perform 5G base station deployment integration according to the 5G network resource allocation data, thereby obtaining 5G base station deployment data; Perform network topology analysis based on 5G base station deployment data to obtain a 5G network topology model; Step S2: dividing the 5G network topology model into base station network coverage hotspot areas according to the 5G network resource allocation data, thereby obtaining base station network coverage hotspot area data, and performing spectrum utilization calculation on the base station network coverage hotspot area data, thereby obtaining base station coverage hotspot area spectrum utilization data; Step S3: Performing coverage area network performance evaluation based on the spectrum utilization data of the base station coverage hotspot area, thereby obtaining coverage area network performance evaluation data; performing frequency band allocation optimization based on the coverage area network performance evaluation data, thereby obtaining coverage area frequency band optimization data; Step S4: extracting 5G base station radio frequency features from the 5G base station deployment data to obtain 5G base station radio frequency data, and optimizing the base station radio frequency configuration of the 5G base station radio frequency data according to the spectrum utilization rate data of the base station coverage hotspot area to obtain base station radio frequency optimization data; Step S5: Optimize the hotspot area resource configuration of the 5G network resource allocation data according to the base station radio frequency optimization data and the coverage area frequency band optimization data, so as to obtain the hotspot area resource optimization configuration data, and upload it to the 5G network communication management platform to perform the configuration optimization task.

2. The method for configuring 5G network functions according to claim 1, characterized in that: Step S1 is specifically as follows: Step S11: Acquire 5G network resource allocation data, and extract 5G base station identification features from the 5G network resource allocation data, thereby obtaining 5G base station identification data; Step S12: extracting 5G base station resource allocation data from 5G network resource allocation data according to the 5G base station identification data, thereby obtaining 5G base station resource allocation data; Step S13: performing 5G base station deployment integration on the 5G base station resource allocation data and the 5G base station identification data, thereby obtaining 5G base station deployment data; Step S14: Perform network topology analysis on the 5G base station deployment data to obtain a 5G network topology model.

3. The method for configuring 5G network functions according to claim 2, characterized in that: Step S14 is specifically as follows: Step S141: extracting 5G network node connection features according to 5G network resource allocation data, thereby obtaining 5G network node connection data; Step S142: performing node connection statistics on the 5G network node connection data, thereby obtaining high-frequency connection node data and low-frequency node connection data; Step S143: performing node association on the 5G base station deployment data according to the high-frequency connection node data and the low-frequency node connection data, thereby obtaining the high-frequency connection base station data and the low-frequency connection base station data; Step S144: performing network connection topology analysis based on the high-frequency connection base station data, thereby obtaining a relay base station network structure model; The network connection topology structure is analyzed based on the low-frequency connection base station data to obtain the edge base station network structure model; Step S145: spatially merge the relay base station network structure model and the edge base station network structure model to obtain a 5G network topology model.

4. The method for configuring 5G network functions according to claim 1, characterized in that: Step S2 is specifically as follows: Step S21: extracting base station signal power features and antenna pattern features from 5G base station deployment data, thereby obtaining base station signal power data and antenna pattern data; Step S22: Calculate the base station coverage range according to the base station signal power data and the antenna pattern data, thereby obtaining the base station coverage range data; Step S23: dividing the 5G network topology model into network hotspot areas according to the 5G network resource allocation data, thereby obtaining 5G network hotspot area data; Step S24: spatially associate the base station coverage data and the 5G network hotspot area data to obtain the base station network coverage hotspot area data; Step S25: Calculate the spectrum utilization of the base station network coverage hotspot area data according to the 5G network resource allocation data, so as to obtain the spectrum utilization data of the base station coverage hotspot area.

5. The method for configuring 5G network functions according to claim 4, characterized in that: Step S23 is specifically as follows: Step S231: Evaluate the base station space density of the 5G network topology model to obtain base station space density data; Step S232: dividing the 5G network topology model into high base station density areas according to the base station spatial density data, thereby obtaining high base station density area data; Step S233: Calculate the resource allocation ratio according to the 5G network resource allocation data, so as to obtain the resource allocation ratio data; Step S234: clustering the 5G network resource allocation data into high-ratio resource allocation areas according to the resource allocation ratio data, thereby obtaining high-ratio resource allocation area data; Step S235: Perform regional intersection calculation on the high base station density area data and the high ratio resource allocation area data to obtain 5G network hotspot area data.

6. The method for configuring 5G network functions according to claim 5, characterized in that: Step S3 is specifically as follows: Step S31: classifying the spectrum utilization rate based on the spectrum utilization rate data of the base station coverage hotspot area, thereby obtaining high spectrum utilization rate area data and low spectrum utilization rate area data; Step S32: integrating spectrum utilization waveform characteristics according to spectrum utilization data of base station coverage hotspot areas, thereby obtaining spectrum utilization waveform characteristic data; Step S33: performing regional spectrum waveform continuity statistics on the spectrum utilization rate waveform feature data, thereby obtaining high-continuity waveform spectrum regional data and low-continuity waveform spectrum regional data; Step S34: performing a regional intersection operation on the high spectrum utilization area data and the high continuity waveform spectrum area data, so as to obtain high network performance coverage area data; performing a regional intersection operation on the low spectrum utilization area data and the low continuity waveform spectrum area data, so as to obtain low network performance coverage area data; Step S35: performing regional spatial merging on the low network performance coverage area data and the high network performance coverage area data, thereby obtaining coverage area network performance evaluation data; Step S36: Optimize frequency band allocation according to the coverage area network performance evaluation data, so as to obtain coverage area frequency band optimization data.

7. The method for configuring 5G network functions according to claim 6, characterized in that: Step S36 is specifically as follows: Step S361: classifying the performance evaluation areas according to the coverage area network performance evaluation data, thereby obtaining low network performance coverage area data and high network performance coverage area data; Step S362: extracting spectrum utilization features from the low network performance coverage area data and the high network performance coverage area data respectively, thereby obtaining low network performance spectrum utilization data and high network performance spectrum utilization data; Step S363: performing spectrum utilization distribution statistics on the low network performance spectrum utilization data and the high network performance spectrum utilization data, thereby obtaining frequency band utilization distribution data; Step S364: Calculate the coverage difference of the low network performance coverage area data and the high network performance coverage area data, so as to obtain coverage area difference data; Step S365: extracting regional frequency band allocation features from the 5G network resource allocation data, thereby obtaining regional frequency band allocation data; Step S366: performing low-performance regional frequency band allocation compensation on the regional frequency band allocation data according to the frequency band utilization distribution data and the coverage area difference data, thereby obtaining coverage area frequency band optimization data.

8. The method for configuring 5G network functions according to claim 1, characterized in that: Step S4 is specifically as follows: Step S41: extracting 5G base station radio frequency features from 5G base station deployment data, thereby obtaining 5G base station radio frequency data; Step S42: performing spectrum utilization distribution statistics on the spectrum utilization data of the base station coverage hotspot area, thereby obtaining base station frequency band utilization distribution data; Step S43: performing congestion evaluation on the base station frequency band utilization distribution data, thereby obtaining frequency band congestion data; Step S44: Optimizing radio frequency parameters of 5G base station radio frequency data according to the frequency band congestion data, thereby obtaining an optimized radio frequency parameter group; Step S45: performing radio frequency simulation on the optimized radio frequency parameter group, thereby obtaining optimized radio frequency parameter simulation data; Step S46: selecting an energy efficiency optimization parameter group for the optimized radio frequency parameter simulation data, thereby obtaining base station radio frequency optimization data.

9. A configuration system for 5G network functions, characterized in that: For executing the configuration method of the 5G network function according to claim 1, the configuration system of the 5G network function comprises: A topology analysis module is used to obtain 5G network resource allocation data, and perform 5G base station deployment integration based on the 5G network resource allocation data, thereby obtaining 5G base station deployment data; perform network topology analysis based on the 5G base station deployment data, thereby obtaining a 5G network topology model; A coverage hotspot area division module is used to divide the base station network coverage hotspot area of ​​the 5G network topology model according to the 5G network resource allocation data, thereby obtaining the base station network coverage hotspot area data, and to calculate the spectrum utilization rate of the base station network coverage hotspot area data, thereby obtaining the spectrum utilization rate data of the base station coverage hotspot area; The frequency band allocation optimization module is used to evaluate the network performance of the coverage area according to the spectrum utilization data of the base station coverage hotspot area, so as to obtain the network performance evaluation data of the coverage area; optimize the frequency band allocation according to the network performance evaluation data of the coverage area, so as to obtain the frequency band optimization data of the coverage area; The base station radio frequency configuration optimization module is used to extract 5G base station radio frequency features from 5G base station deployment data to obtain 5G base station radio frequency data, and optimize the base station radio frequency configuration of the 5G base station radio frequency data based on the spectrum utilization rate data of the base station coverage hotspot area to obtain base station radio frequency optimization data; The regional resource configuration optimization module is used to optimize the hotspot area resource configuration of the 5G network resource allocation data according to the base station radio frequency optimization data and the coverage area frequency band optimization data, so as to obtain the hotspot area resource optimization configuration data and upload it to the 5G network communication management platform to perform the configuration optimization task.

10. A network device, characterized in that: It includes a network device main body, a power supply unit and an electrical control unit. The power supply unit is installed inside the network device main body. The electrical control unit is electrically connected to the power supply unit. The electrical control unit is used to charge and control the network device main body. The electrical control unit is used to execute the configuration method of the 5G network function as described in any one of claims 1-8.

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