An interference intelligent troubleshooting and hierarchical optimization system for sea-land integrated 5G private network

Abstract

The application discloses an interference intelligent troubleshooting and hierarchical optimization system for an integrated sea-land 5G private network, comprising a data acquisition module, a region division module, a benchmark generation module, a level determination module, a collaborative management and control module, and a strategy execution module; the data acquisition module is used to acquire interference data and environmental data; the region division module is used to divide the coverage area into multiple geographical regions; the benchmark generation module is used to generate interference benchmark values and environmental weight values for each geographical region; the level determination module is used to generate interference levels for each geographical region; the collaborative management and control module is used to acquire the interference levels of each geographical region; and the strategy execution module is used to call corresponding optimization strategies and execute them. Thus, by generating differentiated interference benchmark values and environmental weight values for different geographical regions and correcting the interference levels in combination with the positioning information of cross-domain interference sources, the rationality of interference level evaluation and the collaboration of cross-domain interference processing in a sea-land multi-region scenario are effectively improved.

Description

Technical Field

[0001] This application relates to the technical field of wireless communication network management, and in particular to an intelligent interference detection and hierarchical optimization system for integrated land and sea 5G private networks. Background Technology

[0002] A land-sea integrated 5G private network is a dedicated network system that provides coverage and services to both land and near-shore / deep-sea areas. It can be applied to land-sea collaborative scenarios such as smart ports, marine ranches, offshore wind power, and ocean monitoring. This type of network typically needs to balance the dual requirements of dense land coverage and ultra-long-range sea coverage within the same system architecture. Currently, interference management and optimization technologies for 5G private networks are mainly based on propagation models and interference characteristics designed for single scenarios. Their core logic includes detecting interference signals at the base station, determining the type of interference, and adjusting corresponding anti-interference strategies. While these solutions have been applied to some extent in purely land or purely sea scenarios, their adaptability is still insufficient when facing mixed coverage needs across multiple land and sea areas.

[0003] In practical deployments, it has been found that the aforementioned schemes employing a unified evaluation logic often fail to maintain consistent evaluation results in cross-regional scenarios. Those skilled in the art have attempted to introduce dynamic monitoring and statistical analysis methods for signal quality indicators in order to establish relatively unified rules for judging the severity of interference under different environments. Such methods are feasible in principle, capable of reflecting the impact of some environmental factors on signal quality based on measured data. However, in practice, they still face objective difficulties. The wireless propagation environments in sea and land regions differ significantly at the physical level in terms of reflection characteristics, diffraction capabilities, and signal fluctuation amplitude. This leads to a large deviation between the evaluation results produced by the same set of evaluation standards in sea and land areas and the actual severity of interference, making it difficult to establish a universally applicable mapping relationship through simple monitoring and statistical methods. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, one objective of this application is to provide an intelligent interference investigation and hierarchical optimization system for integrated land and sea 5G private networks. By generating differentiated interference benchmark values ​​and environmental weight values ​​for different geographical regions, and combining the location information of cross-domain interference sources to correct the interference level, the system effectively improves the rationality of interference level assessment and the synergy of cross-domain interference handling in multi-regional land and sea scenarios.

[0006] To achieve the above objectives, the first aspect of this application proposes an intelligent interference investigation and hierarchical optimization system for integrated land and sea 5G private networks, including a data acquisition module, a region division module, a benchmark generation module, a level determination module, a collaborative management and control module, and a strategy execution module.

[0007] The data acquisition module is used to obtain interference data and environmental data from base stations within the coverage area of ​​the integrated land and sea 5G private network;

[0008] The region division module is used to divide the coverage area into multiple geographical regions according to the distance from the coastline.

[0009] The benchmark generation module is used to generate interference benchmark values ​​for each geographical region based on the interference data of each geographical region, and to generate environmental weight values ​​for each geographical region based on the environmental data of each geographical region.

[0010] The level determination module is used to generate the interference level of each geographical region based on the interference data, the interference baseline value, and the environmental weight value.

[0011] The collaborative management module is used to obtain the interference level of each geographical region. When the interference level of the first geographical region reaches level 3 or level 4, the collaborative management module locates the second geographical region where the interference source is located in the coverage area according to the interference data of the first geographical region, and corrects the interference level of the first geographical region according to the interference level of the second geographical region to obtain the global interference level.

[0012] The strategy execution module is used to call and execute the corresponding optimization strategy according to the global interference level.

[0013] In addition, the interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks proposed in this application may also have the following additional technical features:

[0014] In one embodiment of this application, the interference data includes uplink received noise floor data;

[0015] The reference generation module collects the uplink received noise floor values ​​of base stations in each geographical region during interference-free periods, and performs statistical analysis on the collected uplink received noise floor values ​​to obtain the average noise floor value for each geographical region. and the standard deviation of the noise floor ,in For geographic region indexing;

[0016] The benchmark generation module will As a reference value for interference in each geographical region.

[0017] In one embodiment of this application, the interference data further includes signal-to-interference-plus-noise ratio data, physical resource block occupancy rate data, and block error rate data;

[0018] The level determination module uses the physical resource block occupancy rate data, the block error rate data, and the reciprocal of the signal-to-interference-plus-noise ratio data as the physical layer interference index value. ;

[0019] The level determination module will determine the physical layer interference index value. With the environmental weight value Multiply by the product to obtain the interference score for each geographical region. ,in For time;

[0020] The level determination module assigns the interference score to each geographical region. Compare with the aforementioned interference baseline values ​​for each geographic region:

[0021] when At that time, the level determination module will determine the interference level as level 1;

[0022] when At that time, the level determination module will determine the interference level as level 2;

[0023] when At that time, the level determination module will determine the interference level as level 3;

[0024] when At that time, the level determination module will determine the interference level as level 4.

[0025] In one embodiment of this application, the environmental data includes sea state data, meteorological data, and atmospheric waveguide monitoring data;

[0026] The benchmark generation module generates static weights for each geographic region based on its distance from the coastline. Dynamic weights for each geographical region are generated based on the sea state data, meteorological data, and atmospheric waveguide monitoring data for each region. ;

[0027] The benchmark generation module will use the static weights of each geographical region. With the dynamic weights Multiply by each other to obtain the environmental weight value for each geographical region. .

[0028] In one embodiment of this application, the region division module divides the plurality of geographical regions in the following manner:

[0029] Areas located at a distance greater than 0 kilometers and less than or equal to 20 kilometers from the coastline are designated as nearshore areas.

[0030] Areas located more than 20 kilometers but less than or equal to 50 kilometers from the coastline are designated as offshore areas.

[0031] Areas more than 50 kilometers from the coastline are designated as ultra-deep sea areas.

[0032] Areas less than or equal to 0 kilometers from the coastline are designated as land areas;

[0033] The benchmark generation module generates the static weights for each geographic region in the following manner. :

[0034] land area It is 1.0;

[0035] offshore areas It is 0.7;

[0036] offshore area It is 0.6;

[0037] ultra-deep sea area It is 0.5.

[0038] In one embodiment of this application, the benchmark generation module generates the dynamic weights in the following manner. :

[0039] When the wave height value in the sea state data is greater than 2 meters, the benchmark generation module will use the dynamic weights. Increased by 10%;

[0040] When the atmospheric waveguide monitoring data indicates the presence of an atmospheric waveguide, the benchmark generation module will use the dynamic weights. Increased by 20%;

[0041] When the humidity value in the meteorological data is greater than 80% and the temperature value is less than 15 degrees Celsius, the benchmark generation module will use the dynamic weights. Increased by 15%.

[0042] In one embodiment of this application, the area division module further delineates a transition zone between the land and sea boundaries within a range of 0 km to 5 km from the coastline.

[0043] Within the land-sea boundary transition zone, the benchmark generation module generates transition zone environmental weight values ​​in the following manner. :

[0044]

[0045] in This represents the distance from the center point of the geographical region to the coastline. For the static weights of the land region, For the static weights of the nearshore area, , where e is the natural constant.

[0046] In one embodiment of this application, the collaborative control module locates the second geographical area where the interference source is located in the following manner:

[0047] The collaborative control module calls the propagation loss model corresponding to each candidate geographical region based on the location coordinates of the first geographical region and the location coordinates of each candidate geographical region, calculates the path loss value of the interference signal propagating from each candidate geographical region to the first geographical region, and positions the candidate geographical region with the smallest path loss value as the second geographical region.

[0048] In one embodiment of this application, the collaborative management module corrects the interference level of the first geographical area in the following manner:

[0049] When the interference level of the second geographical region is lower than that of the first geographical region, the collaborative management module reduces the interference level of the first geographical region by one level, which is then used as the global interference level.

[0050] When the interference level of the second geographical region is higher than that of the first geographical region, the collaborative management module raises the interference level of the first geographical region by one level, which is then used as the global interference level.

[0051] When the interference level of the second geographical region is equal to the interference level of the first geographical region, the collaborative management module uses the interference level of the first geographical region as the global interference level.

[0052] In one embodiment of this application, when the global interference level is level 1, the optimization strategy invoked by the strategy execution module is to adjust the transmission power of the base station in the first geographical area;

[0053] When the global interference level is level 2, the optimization strategy invoked by the strategy execution module is to switch the operating frequency band of the base station in the first geographical area to the backup frequency band.

[0054] When the global interference level is level 3, the optimization strategy called by the strategy execution module is to switch the base stations in the first geographical area to the inter-frequency private network;

[0055] When the global interference level is level 4, the optimization strategy invoked by the policy execution module is to migrate services within the first geographical area to base stations in adjacent geographical areas.

[0056] Compared with the prior art, this application has at least the following beneficial effects:

[0057] 1. This application generates differentiated interference baseline values ​​and environmental weight values ​​for different geographical regions, enabling the same physical layer interference index to correspond to different interference level judgment results under different propagation environments. Compared with a scheme using a unified evaluation standard, this method can reflect the physical layer differences between land and sea areas in terms of reflection characteristics, diffraction capabilities, and signal fluctuation amplitudes. This helps reduce the probability of false alarms caused by natural signal fluctuations in marine scenarios, while avoiding the masking of sudden interference in land scenarios due to excessively high threshold settings.

[0058] 2. This application, through the location of cross-domain interference sources and the cross-regional correction of interference levels, enables the determination of interference levels to comprehensively consider the actual states of both the interference source and the affected end. When the interference source and the affected end are located in different sea and land areas, this mechanism helps to collaboratively formulate optimization strategies from both the source and affected ends, avoiding local optimization methods that only target the affected end.

[0059] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0060] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0061] Figure 1 This is a block diagram of an intelligent interference detection and hierarchical optimization system for an integrated land and sea 5G private network according to an embodiment of this application.

[0062] As shown in the figure: 100, Data Acquisition Module; 200, Region Division Module; 300, Baseline Generation Module; 400, Level Determination Module; 500, Collaborative Management and Control Module; 600, Strategy Execution Module. Detailed Implementation

[0063] Embodiments of this application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. Rather, embodiments of this application include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0064] The following description, in conjunction with the accompanying drawings, describes an embodiment of the present application of an intelligent interference detection and hierarchical optimization system for an integrated land and sea 5G private network.

[0065] like Figure 1As shown in the figure, an intelligent interference investigation and hierarchical optimization system for a land-sea integrated 5G private network according to an embodiment of this application includes a data acquisition module 100, a region division module 200, a benchmark generation module 300, a level determination module 400, a collaborative management and control module 500, and a strategy execution module 600.

[0066] The data acquisition module 100 is deployed within the coverage area of ​​the integrated land-sea 5G private network, establishing data connections with each base station within the coverage area to acquire interference and environmental data from each base station. The region division module 200 is connected to both the data acquisition module 100 and the baseline generation module 300, acquiring geographical location information of the coverage area from the data acquisition module 100 and dividing the coverage area into multiple geographical regions based on its distance from the coastline. The baseline generation module 300 is connected to the data acquisition module 100, the region division module 200, and the level determination module 400, acquiring the division results of each geographical region from the region division module 200, acquiring interference and environmental data within each geographical region from the data acquisition module 100, generating interference baseline values ​​for each geographical region based on the interference data, and generating environmental weight values ​​for each geographical region based on the environmental data. The level determination module 400 is connected to the data acquisition module 100, the baseline generation module 300, and the collaborative management module 500, respectively. It acquires interference data from the data acquisition module 100, obtains interference baseline values ​​and environmental weight values ​​for each geographical area from the baseline generation module 300, and generates the interference level for each geographical area based on the aforementioned data. The collaborative management module 500 is connected to the data acquisition module 100, the level determination module 400, and the policy execution module 600, respectively. It acquires the interference level for each geographical area from the level determination module 400, acquires interference data for the first geographical area from the data acquisition module 100, locates the second geographical area containing the interference source within the coverage area, and corrects the interference level of the first geographical area based on the interference level of the second geographical area to obtain the global interference level. The policy execution module 600 is connected to the collaborative management module 500, acquires the global interference level from the collaborative management module 500, and calls and executes the corresponding optimization policy based on the global interference level.

[0067] It should be noted that, in this embodiment, the above modules can be integrated into the same physical device or distributed across multiple physical devices and communicate via wired or wireless networks. This application does not limit this.

[0068] In one embodiment of this application, the data acquisition module 100 is used to acquire interference data and environmental data from base stations within the coverage area of ​​the integrated land and sea 5G private network.

[0069] Interference data refers to physical quantities and network performance indicators that reflect the degree to which unwanted signals affect desired signals in a wireless communication link. Environmental data refers to parameters that reflect the natural environment and propagation conditions of the base station's geographical location.

[0070] Specifically, the data acquisition module 100 acquires the aforementioned data through data acquisition probes deployed at each base station. The data acquisition probes establish data interfaces with the base station's network management system or baseband processing unit, and read various measurement reports and performance statistics generated in real time during the base station's operation according to a set sampling period.

[0071] In one embodiment of this application, the data acquisition module 100 is connected to the network management system of the base station through the northbound interface of the base station, and reads the physical layer measurement data reported by the base station at a sampling period of once every millisecond.

[0072] In another embodiment, the data acquisition module 100 acquires raw time-domain and frequency-domain signal data through the CPRI (General Common Radio Interface) interface between the baseband processing unit and the radio frequency unit of the base station.

[0073] After acquiring the aforementioned data, the data acquisition module 100 performs format standardization processing, adds a timestamp and geographic location tag to each data entry, and then stores the processed data uniformly in the integrated land-sea interference database. The geographic location tag is used to identify which base station the data originated from and the geographical area to which that base station belongs.

[0074] For example, suppose the coverage area of ​​the integrated land-sea 5G private network includes a land-based base station A (located in a coastal city 2 kilometers from the coastline) and an offshore base station B (located on a sea platform 15 kilometers from the coastline). The data acquisition module 100 acquires uplink received noise floor data from base station A and base station B respectively. The noise floor value reported by base station A is... The noise floor value reported by base station B is The data acquisition module 100 adds a timestamp "2025-06-08 10:00:00" and geographic location tags "land area - base station A" and "nearshore area - base station B" to these two data sets, and then stores them together in the integrated land-sea interference database.

[0075] The data acquisition module 100 enables unified data collection and storage for base stations across the land and sea areas, breaking down the information silos where land and sea data belong to different management systems, and providing a unified data foundation for subsequent cross-regional interference level assessment and collaborative optimization.

[0076] In one embodiment of this application, the region division module 200 is used to divide the coverage area into multiple geographical regions according to the distance from the coastline.

[0077] In this context, a geographical region refers to a basic unit obtained by dividing the coverage area of ​​the integrated land and sea 5G private network according to geographical location and propagation environment characteristics. Each geographical region has roughly the same propagation environment characteristics. The distance from the coastline refers to the straight-line distance between the center point of the geographical region and the nearest coastline, expressed in kilometers.

[0078] Specifically, the region division module 200 first acquires electronic map data of the coverage area, which includes coastline location information, land topography information, and sea area information. Using the coastline as a baseline on the electronic map, the region division module 200 calculates the distance from the coastline to each location point within the coverage area, and then divides the coverage area into multiple geographical regions according to the following distance intervals:

[0079] Areas located between 0 km and 20 km from the coastline are designated as nearshore areas; areas located between 20 km and 50 km from the coastline are designated as offshore areas; areas located between 50 km and 50 km from the coastline are designated as ultra-offshore areas; and areas located between 0 km and 0 km from the coastline (i.e., on the landward side of the coastline) are designated as land areas.

[0080] For land areas, the region division module 200 further obtains the building density data for that region. Building density refers to the ratio of the building area to the total area of ​​the region, expressed as a percentage. Regions with a building density greater than 30% are classified as urban land areas, and regions with a building density less than or equal to 30% are classified as non-urban land areas.

[0081] Furthermore, the region delineation module 200 also defines a land-sea boundary transition zone within a range of 0 to 5 kilometers from the coastline. This transition zone is a strip-shaped area extending 0 to 5 kilometers from the coastline towards the land, and another strip-shaped area extending 0 to 5 kilometers from the coastline towards the sea. Within this transition zone, the land-based propagation environment and the marine propagation environment intertwine and gradually transition.

[0082] For example, suppose the coverage area of ​​the integrated land-sea 5G private network is a coastal city and its adjacent sea area, with the area ranging from 118.5°E to 119.5°E and 28.5°N to 29.5°N. The area division module 200 obtains electronic map data of this area and divides it based on the local coastline. The urban area within -5 km to 0 km from the coastline (i.e., within 5 km inland from the coastline) is designated as the urban land area within the land area, and this area is also marked as the land-sea boundary transition zone; the sea area within 0 km to 20 km from the coastline is designated as the near-shore area; the sea area within 20 km to 50 km from the coastline is designated as the offshore area; and the sea area more than 50 km from the coastline is designated as the ultra-offshore area.

[0083] By dividing regions according to their distance from the coastline, areas with similar propagation environment characteristics are grouped into the same geographical region, providing a regional division basis for subsequently generating differentiated interference benchmark values ​​and weighting factors for different regions.

[0084] In one embodiment of this application, the benchmark generation module 300 is used to generate interference benchmark values ​​for each geographical region based on interference data of each geographical region, and to generate environmental weight values ​​for each geographical region based on environmental data of each geographical region.

[0085] The interference baseline is a reference line used to assess the severity of interference within a geographical area. The interference baseline includes the mean noise floor. and the standard deviation of the noise floor Two statistics, among which This is a geographic region index used to identify different geographic regions. (Noise floor mean) This reflects the average uplink received noise floor level in the geographical area under interference-free or low-interference conditions; noise floor standard deviation. This reflects the dispersion of the background noise data in this geographical area.

[0086] It should be noted that in wireless communication systems, uplink receiver noise floor is a fundamental physical quantity for measuring interference levels. Noise floor levels vary across different geographical regions due to factors such as propagation environment, equipment noise, and ambient noise. If a uniform noise floor threshold is used to determine interference across the entire region, areas with naturally high noise floors (such as sea areas) will frequently trigger alarms, while areas with naturally low noise floors (such as land) will mask sudden interference. Therefore, it is necessary to establish a benchmark value reflecting the specific noise floor level for each geographical region.

[0087] Specifically, the baseline generation module 300 obtains historical uplink received noise floor data for each base station within each geographical area from the data acquisition module 100. The baseline generation module 300 first filters out interference-free periods from the historical data. The criteria for determining interference-free periods are: the time period during which the base station's traffic volume is less than 30% of its average daily traffic volume, and the base station does not receive any interference alarms. In practice, 00:00 to 06:00 is typically selected as the interference-free period.

[0088] During interference-free periods in each geographical area, the reference generation module 300 collects the uplink received noise floor values ​​of each base station within that geographical area, obtaining a set of noise floor sample data. The reference generation module 300 then performs statistical analysis on this set of sample data: calculating the arithmetic mean of all samples as the mean noise floor value for that geographical area. Calculate the standard deviation of all samples, which will be used as the noise floor standard deviation for that geographic region. .

[0089] The benchmark generation module 300 will As a reference value for interference in each geographical region.

[0090] Continuing with the previous example, let's assume the nearshore area... 1000 uplink receive noise floor samples were collected during the interference-free period, with a sample mean of [missing value]. The sample standard deviation is The interference reference value for the nearshore area is... .

[0091] Assuming urban land area 1000 uplink receive noise floor samples were collected during the interference-free period, with a sample mean of [missing value]. The sample standard deviation is The interference baseline value for the urban land area is then... .

[0092] It can be seen that the interference benchmark value in the nearshore area The interference benchmark value is higher than that of urban land areas. This reflects the objective fact that the noise level in the sea is naturally higher than that on land.

[0093] By establishing interference baseline values ​​for each geographic region based on its own historical data, the criteria for determining interference levels can reflect the natural differences in the background noise levels of each region, thus avoiding the problems of frequent false alarms in the sea and the masking of sudden interference in the land due to a uniform threshold.

[0094] It should be noted that the environmental weight value This is a dimensionless numerical value used for contextualized correction of physical layer interference indicators. A larger environmental weight value indicates a higher likelihood that the same physical layer interference indicator will be classified as a higher interference level in that geographic area. The environmental weight value is determined by static weights. and dynamic weights Multiplying the two parts together, we get the result where Indicates time.

[0095] Static weights These weights are determined based on the inherent attributes of a geographical region (such as distance from the coastline, topographic features, etc.) and remain unchanged over a long timescale. Dynamic weights It is a weighted component that is dynamically adjusted based on real-time environmental data (such as sea state, weather, atmospheric waveguide status, etc.) and changes over time.

[0096] It should also be noted that the wireless propagation environment differs fundamentally between land and sea. At sea, strong reflection and weak scattering result in large signal fluctuations; on land, due to building obstruction and the presence of numerous scattering objects, the signal is relatively stable. Relying solely on interference baseline values ​​is insufficient to completely eliminate the impact of these differences on interference level determination. By introducing environmental weight values, the physical layer interference indicators can be weighted and corrected, making the determination results more closely reflect the actual propagation characteristics of each region.

[0097] Specifically, the baseline generation module 300 obtains the region type information of each geographic region from the region division module 200, and configures static weights for each geographic region according to the region type. :

[0098] For urban land areas The value is 1.0;

[0099] For non-urban land areas The value is 0.9;

[0100] For offshore areas, The value is 0.7;

[0101] For the open sea area, The value is 0.6;

[0102] For ultra-deep sea areas The value is 0.5.

[0103] The above static weight values ​​are set based on the following: signal fluctuations in land areas are relatively small, so the weight values ​​are higher and the physical layer interference indicators are amplified less; signal fluctuations in sea areas are relatively large, so the weight values ​​are lower and the physical layer interference indicators are amplified more, thereby avoiding frequent misjudgments caused by natural signal fluctuations.

[0104] In one embodiment of this application, the benchmark generation module 300 acquires environmental data of each geographical region in real time from the data acquisition module 100. The environmental data includes sea state data, meteorological data, and atmospheric waveguide monitoring data.

[0105] The benchmark generation module 300 generates dynamic weights according to the following rules. :

[0106] Sea state factor: The reference generation module 300 monitors wave height values ​​in sea state data. Wave height refers to the vertical height difference between the crest and trough of a wave, measured in meters. When the wave height value is greater than 2 meters, it indicates a high sea surface roughness and increased signal reflection loss. The reference generation module 300 will then dynamically weight... Increased by 10%.

[0107] Atmospheric ducting factor: The benchmark generation module 300 monitors atmospheric ducting data. Atmospheric ducting refers to an abnormal propagation structure in the atmosphere formed due to temperature or humidity variations with altitude. Within this structure, radio waves can be trapped and propagate horizontally over long distances. When atmospheric ducting monitoring data indicates the presence of atmospheric ducting, it means that interference signals may propagate to even greater distances through ducting effects, expanding the area of ​​influence. The benchmark generation module 300 will dynamically weight... Increased by 20%.

[0108] Meteorological factors: The benchmark generation module 300 monitors humidity and temperature values ​​in meteorological data. Humidity values ​​are expressed as a percentage, and temperature values ​​are expressed in degrees Celsius. When the humidity value is greater than 80% and the temperature value is less than 15 degrees Celsius, it indicates that the atmosphere is in a high-humidity, low-temperature state, which is conducive to the formation of a temperature inversion layer and atmospheric waveguide. The benchmark generation module 300 dynamically weights these parameters. Increased by 15%.

[0109] The above factors can take effect simultaneously. For example, when the wave height is greater than 2 meters and an atmospheric waveguide is present, the dynamic weighting... Both rates were increased by 10% and 20%, resulting in a cumulative increase of 30%.

[0110] The benchmark generation module 300 assigns static weights to each geographic region. With dynamic weights Multiply to obtain the geographical regions in Environment weight value at time :

[0111]

[0112] As a possible scenario, within the land-sea boundary transition zone, the propagation environment lies between purely land and purely sea. To avoid abrupt changes in interference levels due to sudden weight shifts at the land-sea boundary, the baseline generation module 300 employs a gradual weight transition mechanism within the land-sea boundary transition zone.

[0113] The baseline generation module 300 obtains the distance from the center point of the geographic region within the transition zone to the coastline. (Unit: kilometers) The environmental weight value of the transition zone is generated according to the following formula. :

[0114]

[0115] in, The static weight for the land region is set to 1.0. The static weight for the nearshore area is 0.7. The transition function is monotonically increasing.

[0116]

[0117] in is a natural constant, approximately equal to 2.71828. This transition function is an sigmoid function, when... hour, Approximately equal to 0.23, the weight is close to the land weight; when hour, It is approximately equal to 0.77, with a weight close to that of the sea area; in place, The weight is the midpoint between the land weight and the sea weight.

[0118] Continuing with the previous example, the static weight of the nearshore area At the current moment, the wave height in the sea state data is 2.5 meters (>2 meters), atmospheric duct monitoring data indicates the presence of atmospheric ducting, and the humidity in the meteorological data is 85% (>80%) and the temperature is 12 degrees Celsius (<15 degrees Celsius). Therefore, the dynamic weighting... Environmental weight value of the nearshore area at the current moment. .

[0119] By using static weights to reflect the differences in the inherent propagation characteristics of each region, and dynamic weights to reflect the impact of real-time changes in environmental factors on interference propagation, and by using progressive weights in the transition zone to avoid level jumps at the land-sea boundary, the interference level determination results are more in line with the actual propagation environment.

[0120] In one embodiment of this application, the level determination module 400 is used to generate the interference level of each geographical area based on interference data, interference baseline value and environmental weight value.

[0121] Among them, physical layer interference index value It is a comprehensive numerical value reflecting the intensity of physical layer interference, composed of the physical resource block occupancy rate data, block error rate data, and the reciprocal of the signal-to-interference-plus-noise ratio data. Interference Score This is a value obtained by correcting the physical layer interference index value for environmental weights. It is used to compare with the interference baseline value to determine the interference level. The interference level is a discrete level used to characterize the severity of interference, including four levels: Level 1, Level 2, Level 3, and Level 4. The higher the level, the more severe the interference.

[0122] It should be noted that a single physical layer indicator is insufficient to fully reflect the actual impact of interference. Physical resource block occupancy reflects the degree of spectrum resource utilization, block error rate reflects the reliability of data transmission, and signal-to-interference-plus-noise ratio (SINR) reflects the relative strength of the signal and the interference plus noise. Combining these three factors into a physical layer interference indicator value allows for a more comprehensive assessment of the interference situation. Furthermore, multiplying this comprehensive indicator by an environmental weight value allows the assessment results to be adapted to the propagation environment characteristics of different regions.

[0123] Specifically, the level determination module 400 acquires physical resource block occupancy rate data, block error rate data, and signal-to-interference-plus-noise ratio (SIR / NOT) data for each geographical region from the data acquisition module 100. The level determination module 400 uses the reciprocals of these data as the physical layer interference index value. .

[0124] In one embodiment of this application, the physical layer interference index value Calculate using a weighted summation method:

[0125]

[0126] in, This represents the physical resource block occupancy rate (value range: 0~1). The error rate is the block error rate (value range 0~1). Signal-to-interference-plus-noise ratio (SIR / NOT) (unit: linear, nonlinear) value), These are preset weighting coefficients, and the sum of the three is 1. In one specific embodiment, .

[0127] Specifically, the rating module 400 obtains the environmental weight values ​​of each geographical region from the baseline generation module 300. Physical layer interference index value Environmental weight value Multiply by the product to obtain the interference score for each geographical region. :

[0128]

[0129] The rating module 400 obtains the mean noise floor value of each geographic region from the baseline generation module 300. and the standard deviation of the noise floor Distance score for each geographical region Interference baseline values ​​for each geographical region ( +k× Compare the values ​​of k=1,3,5, and determine the interference level according to the following branch conditions:

[0130] when At that time, the level determination module 400 determines the interference level of the geographical area as level 1;

[0131] when At that time, the level determination module 400 determines the interference level of the geographical area as level 2;

[0132] when At that time, the level determination module 400 determines the interference level of the geographical area as level 3;

[0133] when At that time, the level determination module 400 determines the interference level of the geographical area as level 4.

[0134] Continuing with the previous example, let's assume the nearshore area ( =1) At the current moment, the physical resource block occupancy rate is 0.6, the block error rate is 0.05, and the signal-to-interference-plus-noise ratio (linear value) is 10 (i.e., 10dB). Then the physical layer interference index value is... .

[0135] Environmental weight values ​​of the nearshore area at the current moment =1.015, then the interference score is... =0.235×1.015≈0.238.

[0136] Will The interference level of the geographical area is determined by comparing it with the interference baseline value.

[0137] By integrating multiple physical layer indicators into a physical layer interference index value and then correcting it with an environmental weight value, the interference level determination results are more comprehensive and accurate, avoiding the one-sidedness of a single indicator.

[0138] In one embodiment of this application, the collaborative management module 500 is used to obtain the interference level of each geographical region. When the interference level of the first geographical region reaches level 3 or level 4, the collaborative management module 500 locates the second geographical region where the interference source is located within the coverage area based on the interference data of the first geographical region, and corrects the interference level of the first geographical region based on the interference level of the second geographical region to obtain the global interference level.

[0139] The first geographical region refers to any geographical region where the interference level reaches level 3 or 4, i.e., the geographical region most severely affected by interference. The second geographical region refers to the geographical region where the interference source is located. The global interference level is the final interference level determined after comprehensively considering the states of both the interference source and the affected end, and is used to guide the execution of optimization strategies.

[0140] It should be noted that when the interference level reaches Level 3 or Level 4, the interference has already caused a relatively serious impact on services, requiring the location of the interference source and intervention at the source. However, the interference source may be located in a different geographical area from the affected end (e.g., marine radar interfering with a land base station), and data from the affected end alone cannot fully assess the true extent of the interference. Therefore, it is necessary to locate the second geographical area where the interference source is located, and to adjust the interference level of the first geographical area based on the interference status of the second geographical area, so that the final determined global interference level can reflect the overall situation of cross-domain interference.

[0141] Specifically, the collaborative control module 500 acquires interference data within the first geographical area from the data acquisition module 100. Based on the location coordinates of the first geographical area and the location coordinates of each candidate geographical area, the collaborative control module 500 calls the propagation loss model corresponding to each candidate geographical area to calculate the path loss value of the interference signal propagating from each candidate geographical area to the first geographical area.

[0142] Propagation loss models are used to describe the signal attenuation of radio waves as they propagate from the transmitter to the receiver under specific propagation conditions. Different geographical regions use different propagation loss models: inland areas use the urban or rural propagation model from the 3GPP TR38.901 standard; nearshore areas use the dual-ray ground reflection model; and offshore and ultra-offshore areas use a dual-ray model with added evaporation waveguide effect corrections.

[0143] The collaborative control module 500 identifies the candidate geographic region with the lowest path loss value as the second geographic region. The lowest path loss value means that the interference signal attenuates the least as it travels from the candidate region to the first geographic region, indicating that the candidate region is most likely the location of the interference source.

[0144] For example, suppose the first geographic region is an urban land area (the affected end), with an interference level of 3. Candidate geographic regions include nearshore region A (10 km from the first region), offshore region B (30 km from the first region), and another land area C (5 km from the first region). The collaborative control module 500 calls the propagation loss model for each region to calculate the path loss value of the interference signal propagating from each candidate region to the first region. The calculation results show that the path loss value from land area C is 85 dB, from nearshore region A is 72 dB, and from offshore region B is 95 dB. The path loss value is lowest in nearshore region A (72 dB), therefore the collaborative control module 500 identifies nearshore region A as the second geographic region (the region where the interference source is located).

[0145] The interference source is located by comparing path loss based on the propagation loss model. This method utilizes the physical laws of radio wave propagation, does not rely on additional positioning equipment, and is simple and effective.

[0146] In one embodiment of this application, the collaborative management module 500 obtains the interference level of the second geographical region from the level determination module 400. The collaborative management module 500 compares the interference level of the second geographical region with the interference level of the first geographical region and makes corrections according to the following branch conditions:

[0147] When the interference level of the second geographic region is lower than that of the first geographic region, it indicates that the interference level at the source end is lower than that at the affected end. The interference may mainly originate from anomalies in the propagation path (such as atmospheric waveguides). The collaborative control module 500 will reduce the interference level of the first geographic region by one level, which will be used as the global interference level. For example, if the first geographic region is at level 3 and the second geographic region is at level 2, the global interference level will be level 2.

[0148] When the interference level of the second geographical region is higher than that of the first geographical region, it indicates that the interference level at the source is higher than that at the target, and the source is transmitting strong interference. The collaborative control module 500 will raise the interference level of the first geographical region by one level, which will be used as the global interference level. For example, if the first geographical region is at level 3 and the second geographical region is at level 4, the global interference level will be level 4.

[0149] When the interference level of the second geographical region is equal to that of the first geographical region, it means that the interference levels of the interference source and the affected end are comparable. The collaborative control module 500 will take the interference level of the first geographical region as the global interference level and will not make any corrections.

[0150] Continuing with the previous example, the interference level of the first geographical area (urban land area) is level 3, and the interference level of the second geographical area (nearshore area A) is level 2. Since the interference level of the second geographical area (level 2) is lower than the interference level of the first geographical area (level 3), the collaborative control module 500 reduces the interference level of the first geographical area by one level, resulting in a global interference level of level 2.

[0151] By combining the interference status at the interference source end to correct the interference level at the affected end, the final determined global interference level can reflect the overall situation of cross-domain interference, avoiding the problem of unilaterally determining the interference level based solely on the data from the affected end.

[0152] In one embodiment of this application, the policy execution module 600 is used to call and execute the corresponding optimization policy according to the global interference level.

[0153] An optimization strategy refers to a set of pre-configured operational instructions for different interference levels, used to reduce or eliminate the impact of interference. The optimization strategy library is a collection that stores all optimization strategies.

[0154] Specifically, the strategy execution module 600 obtains the global interference level from the collaborative management module 500. The strategy execution module 600 internally stores an optimization strategy library, which contains optimization strategies corresponding to each interference level. The strategy execution module 600 calls the corresponding optimization strategy from the optimization strategy library according to the global interference level and sends the optimization strategy to the corresponding base station or network element for execution.

[0155] The correspondence between strategies and interference levels in the optimization strategy library is as follows:

[0156] When the global interference level is level 1, the optimization strategy called by the policy execution module 600 is to adjust the transmission power of the base stations in the first geographical area. Specifically, the policy execution module 600 sends a power adjustment instruction to the base stations in the first geographical area. The base stations reduce the transmission power by a set value (e.g., 2dB) according to the instruction to reduce interference to adjacent areas.

[0157] When the global interference level is level 2, the optimization strategy called by the policy execution module 600 is to switch the working frequency band of the base station in the first geographical area to the backup frequency band. Specifically, the policy execution module 600 sends a frequency band switching instruction to the base station in the first geographical area. The base station switches its working frequency band from the current frequency band to the pre-configured backup frequency band according to the instruction to avoid the interference frequency band.

[0158] When the global interference level is level 3, the optimization strategy called by the policy execution module 600 is to switch the base stations in the first geographical area to a private network of different frequencies. Specifically, the policy execution module 600 sends a private network switching instruction to the base stations in the first geographical area. The base stations switch from the current network to the private network of different frequencies (i.e., use a private network of different frequencies) according to the instruction to completely avoid interference.

[0159] When the global interference level is level 4, the optimization strategy called by the policy execution module 600 is to migrate the services in the first geographical area to the base station in the adjacent geographical area. Specifically, the policy execution module 600 sends a service migration instruction to the base station in the first geographical area. The base station then migrates the currently carried services to the base station in the adjacent geographical area with better interference through a handover process, in order to ensure the continuity of services.

[0160] Continuing the previous example, the global interference level is Level 2. The policy execution module 600 retrieves the optimization policy corresponding to Level 2 from the optimization policy library to switch the operating frequency band of the base station in the first geographical area to the spare frequency band. The policy execution module 600 sends a frequency band switching command to the base station in the urban land area (the first geographical area), the command containing the frequency information of the spare frequency band (e.g., switching from 3.5GHz to 4.9GHz). After receiving the command, the base station executes the frequency band switching operation, switching the operating frequency band to the spare frequency band.

[0161] By establishing a mapping relationship between interference levels and optimization strategies, the selection of optimization strategies is matched with the severity of interference, thus achieving hierarchical processing and avoiding the problems of over-optimization or under-optimization.

[0162] Specifically, the collaborative workflow of each module in this application will be explained below using a complete application scenario.

[0163] Assume a land-sea integrated 5G private network covers a coastal city and its adjacent sea area. The data acquisition module 100 continuously acquires interference and environmental data from each base station within the coverage area and stores it in the land-sea integrated interference database. The area division module 200 divides the coverage area into urban land area, non-urban land area, near-shore area, offshore area, and ultra-offshore area, and sets up a land-sea boundary transition zone within 0-5 kilometers of the coastline.

[0164] The baseline generation module 300 generates interference baseline values ​​(mean noise floor) for each region based on historical noise floor data for each region. and the standard deviation of the noise floor Meanwhile, the benchmark generation module 300 configures static weights according to the region type of each region. Dynamic weights are generated based on real-time sea state data, meteorological data, and atmospheric waveguide monitoring data. This leads to the synthesis of environmental weight values ​​for each region. .

[0165] The level determination module 400 acquires real-time data on physical resource block occupancy, block error rate, and signal-to-interference-plus-noise ratio for each region, and calculates the physical layer interference index value. And combined with environmental weight values Obtain interference score ,Will The interference level of each region is generated in real time by comparing it with the interference baseline value of each region.

[0166] At a certain moment, the level determination module 400 determines that the interference level of the urban land area (first geographic area) has reached level 3. The collaborative management and control module 500 acquires this trigger event, obtains interference data of the urban land area from the data acquisition module 100, and locates the second geographic area where the interference source is located within the coverage area by comparing path loss. Assume the location result is the near-shore area (second geographic area). The collaborative management and control module 500 obtains the interference level of the near-shore area (assumed to be level 2). Since the interference level of the second geographic area (level 2) is lower than the interference level of the first geographic area (level 3), the collaborative management and control module 500 reduces the interference level of the first geographic area by one level, resulting in a global interference level of level 2.

[0167] The strategy execution module 600 calls the corresponding optimization strategy from the optimization strategy library according to the global interference level (level 2), switches the working frequency band of the base station in the first geographical area to the spare frequency band, and executes the strategy.

[0168] In summary, the interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks proposed in this application improves the rationality of interference level assessment and the synergy of cross-domain interference handling in multi-regional land and sea scenarios by generating differentiated interference benchmark values ​​and environmental weight values ​​for different geographical regions and correcting the interference level by combining the location information of cross-domain interference sources.

[0169] In the description of this specification, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0170] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0171] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. An intelligent interference detection and hierarchical optimization system for integrated land and sea 5G private networks, characterized in that, It includes a data acquisition module, a region division module, a baseline generation module, a level determination module, a collaborative management and control module, and a strategy execution module; The data acquisition module is used to obtain interference data and environmental data from base stations within the coverage area of ​​the integrated land and sea 5G private network; The region division module is used to divide the coverage area into multiple geographical regions according to the distance from the coastline. The benchmark generation module is used to generate interference benchmark values ​​for each geographical region based on the interference data of each geographical region, and to generate environmental weight values ​​for each geographical region based on the environmental data of each geographical region. The level determination module is used to generate the interference level of each geographical region based on the interference data, the interference baseline value, and the environmental weight value. The collaborative management module is used to obtain the interference level of each geographical region. When the interference level of the first geographical region reaches level 3 or level 4, the collaborative management module locates the second geographical region where the interference source is located in the coverage area according to the interference data of the first geographical region, and corrects the interference level of the first geographical region according to the interference level of the second geographical region to obtain the global interference level. The strategy execution module is used to call and execute the corresponding optimization strategy according to the global interference level.

2. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 1, characterized in that, The interference data includes uplink received noise floor data; The reference generation module collects the uplink received noise floor values ​​of base stations in each geographical region during interference-free periods, and performs statistical analysis on the collected uplink received noise floor values ​​to obtain the average noise floor value for each geographical region. and floor noise standard deviation ,in For geographic region indexing; The benchmark generation module will As a reference value for interference in each geographical region.

3. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 1, characterized in that, The interference data also includes signal-to-interference-plus-noise ratio data, physical resource block occupancy rate data, and block error rate data; The level determination module uses the physical resource block occupancy rate data, the block error rate data, and the reciprocal of the signal-to-interference-plus-noise ratio data as the physical layer interference index value. ; The level determination module will determine the physical layer interference index value. With the environmental weight value Multiply by the product to obtain the interference score for each geographical region. ,in For time; The level determination module assigns the interference score to each geographical region. Compare with the aforementioned interference baseline values ​​for each geographic region: when At that time, the level determination module will determine the interference level as level 1; when At that time, the level determination module will determine the interference level as level 2; when At that time, the level determination module will determine the interference level as level 3; when At that time, the level determination module will determine the interference level as level 4.

4. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 1, characterized in that, The environmental data includes sea state data, meteorological data, and atmospheric waveguide monitoring data; The benchmark generation module generates static weights for each geographic region based on its distance from the coastline. Dynamic weights for each geographical region are generated based on the sea state data, meteorological data, and atmospheric waveguide monitoring data for each region. ; The benchmark generation module will use the static weights of each geographical region. With the dynamic weights Multiply by each other to obtain the environmental weight value for each geographical region. .

5. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 4, characterized in that, The region division module divides the multiple geographical regions in the following manner: Areas located at a distance greater than 0 kilometers and less than or equal to 20 kilometers from the coastline are designated as nearshore areas. Areas located more than 20 kilometers but less than or equal to 50 kilometers from the coastline are designated as offshore areas. Areas more than 50 kilometers from the coastline are designated as ultra-deep sea areas. Areas less than or equal to 0 kilometers from the coastline are designated as land areas; The benchmark generation module generates the static weights for each geographic region in the following manner. : land area It is 1.0; offshore areas It is 0.7; offshore area It is 0.6; ultra-deep sea area It is 0.

5.

6. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 4, characterized in that, The benchmark generation module generates the dynamic weights in the following manner. : When the wave height value in the sea state data is greater than 2 meters, the benchmark generation module will use the dynamic weights. Increased by 10%; When the atmospheric waveguide monitoring data indicates the presence of an atmospheric waveguide, the benchmark generation module will use the dynamic weights. Increased by 20%; When the humidity value in the meteorological data is greater than 80% and the temperature value is less than 15 degrees Celsius, the benchmark generation module will use the dynamic weights. Increased by 15%.

7. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 5, characterized in that, The area delineation module also delineates a transition zone between the land and sea boundaries within a range of 0 to 5 kilometers from the coastline. Within the land-sea boundary transition zone, the benchmark generation module generates transition zone environmental weight values ​​in the following manner. : in This represents the distance from the center point of the geographical region to the coastline. For the static weights of the land region, For the static weights of the nearshore area, , where e is the natural constant.

8. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 1, characterized in that, The collaborative control module locates the second geographical region where the interference source is located in the following manner: The collaborative control module calls the propagation loss model corresponding to each candidate geographical region based on the location coordinates of the first geographical region and the location coordinates of each candidate geographical region, calculates the path loss value of the interference signal propagating from each candidate geographical region to the first geographical region, and positions the candidate geographical region with the smallest path loss value as the second geographical region.

9. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 1, characterized in that, The collaborative management module corrects the interference level of the first geographical area in the following manner: When the interference level of the second geographical region is lower than that of the first geographical region, the collaborative management module reduces the interference level of the first geographical region by one level, which is then used as the global interference level. When the interference level of the second geographical region is higher than that of the first geographical region, the collaborative management module raises the interference level of the first geographical region by one level, which is then used as the global interference level. When the interference level of the second geographical region is equal to the interference level of the first geographical region, the collaborative management module uses the interference level of the first geographical region as the global interference level.

10. The interference intelligent investigation and hierarchical optimization system for integrated land and sea 5G private networks according to claim 1, characterized in that, When the global interference level is level 1, the optimization strategy invoked by the strategy execution module is to adjust the transmission power of the base stations in the first geographical area; When the global interference level is level 2, the optimization strategy invoked by the strategy execution module is to switch the operating frequency band of the base station in the first geographical area to the backup frequency band. When the global interference level is level 3, the optimization strategy called by the strategy execution module is to switch the base stations in the first geographical area to the inter-frequency private network; When the global interference level is level 4, the optimization strategy invoked by the policy execution module is to migrate services within the first geographical area to base stations in adjacent geographical areas.

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