A wireless network device configuration method and system

Abstract

The application is suitable for the field of wireless communication technology, and provides a wireless network device configuration method and system. The method comprises the following steps: acquiring a basic channel score value of a to-be-allocated channel originating from a signal node to which a to-be-configured terminal is to be configured, simultaneously acquiring a historical operation record of the signal node and tunnel structure information of a tunnel structure to which the signal node belongs. The application dynamically identifies a current structure complexity level value by combining the structural path characteristics between the to-be-configured terminal and the signal node, and takes a representative data retransmission rate in the historical operation record as a reference to construct a level deviation amplitude for correcting the basic channel score value, so as to dynamically optimize the channel score result.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wireless communication, and particularly relates to a wireless network device configuration method and system. BACKGROUND

[0002] In the prior art, in the configuration process of a wireless network device, the signal quality of an available channel is usually scored so as to select a channel resource with better communication quality in the configuration process. The scoring process mainly depends on instant physical parameter indexes of a target channel, such as a received signal strength (RSSI), a signal-to-noise ratio (SNR), an interference intensity, a connection number or a bandwidth utilization, etc. These indexes can reflect the basic transmission state of a channel at a current time point, and are widely applied to conventional scenes such as home WiFi deployment, office network automatic configuration, IoT device initial access, etc. However, in an application scene with a highly complex structure environment, such as a closed tunnel environment, the real-time parameters on which the above method depends often cannot accurately reflect potential attenuation, shielding and multipath interference, etc. in a signal propagation path, resulting in a lack of structural adaptability of the channel scoring result, and finally affecting the access stability of the device and the network transmission quality.

[0003] Especially in a tunnel scene, a wireless signal is comprehensively affected by factors such as wall reflection, metal shielding, cross-pipeline, electromagnetic interference, etc. when propagating in a structural path. These influences are often closely related to the structural composition of the path, and have significant spatial correlation and unpredictability. However, the prior art fails to incorporate the structural complexity of a communication path into the evaluation system in the channel scoring process, and also lacks sufficient analysis of the historical running performance of a channel in a similar structural environment, resulting in poor environmental adaptability of the configuration process. In some complex scenes, even if a channel with a higher score is selected, problems such as unstable signal, frequent retransmission or access failure, etc. may still occur, significantly reducing the device use efficiency and increasing the cost of manual adjustment. SUMMARY

[0004] The present application aims to provide a wireless network device configuration method and system, which aims to solve the problems proposed in the background.

[0005] The present application is implemented as follows. A wireless network device configuration method, the method comprising:

[0006] obtaining a basic channel score value of a to-be-assigned channel originating from a signal node belonging to the signal node and to be configured to a to-be-configured terminal, and simultaneously obtaining a historical running record of the signal node and tunnel structure information of a tunnel structure belonging to the signal node;

[0007] The tunnel structure information is analyzed, the first identification area and the second identification area of the terminal to be configured and the signal node are determined respectively, the spacing path structure between the first identification area and the second identification area is determined, and the current structure complexity level value is determined.

[0008] The historical operation record is analyzed, a plurality of section operation records of the channel to be distributed under different structure complexity level values are extracted, each section operation record is analyzed in sequence, and a matching section operation record in which the data retransmission rate is at the intermediate quantile level is determined.

[0009] The level deviation amplitude between the current structure complexity level value and the structure complexity level value corresponding to the matching section operation record is calculated, and the basic channel score value is corrected according to the level deviation amplitude.

[0010] As a further limitation of the technical scheme of the embodiment of the application, the step of analyzing the tunnel structure information, determining the first identification area and the second identification area of the terminal to be configured and the signal node respectively, and determining the current structure complexity level value based on the spacing path structure between the first identification area and the second identification area comprises:

[0011] The position information of the terminal to be configured and the signal node is obtained.

[0012] The tunnel structure information is analyzed, the first identification area and the second identification area corresponding to the position information of the terminal to be configured and the signal node respectively are determined, and the spacing path structure between the first identification area and the second identification area is obtained.

[0013] The preset reference model is called to match the spacing path structure, so as to determine the current structure complexity level value.

[0014] As a further limitation of the technical scheme of the embodiment of the application, the preset reference model is a reference model for establishing a one-to-one correspondence between the tunnel path structure and the structure complexity level, and the preset reference model comprises the structure complexity level value corresponding to different path lengths, path turning numbers, wall material types, metal coverage ratios of the areas passed through by the path, numbers and distribution densities of signal shielding bodies, and numbers of cross pipelines.

[0015] As a further limitation of the technical scheme of the embodiment of the application, the step of analyzing the historical operation record, extracting a plurality of section operation records of the channel to be distributed under different structure complexity level values, and analyzing each section operation record in sequence to determine a matching section operation record in which the data retransmission rate is at the intermediate quantile level comprises:

[0016] The historical operation record is analyzed, and a plurality of section operation records of the channel to be distributed under different structure complexity level values are extracted.

[0017] The operation record of each segment is analyzed sequentially to determine the data retransmission rate of the channel to be allocated within a preset time period.

[0018] By comparing the data retransmission rates, the matching segment operation records at the middle quantile level are identified.

[0019] As a further limitation of the technical solution of this embodiment of the invention, the step of calculating the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the matching segment operation record, and correcting the basic channel score value according to the level deviation includes:

[0020] Calculate the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching section, and use it as a correction factor;

[0021] The preset channel score correction formula is invoked, and the correction factor is substituted into the formula to correct the basic channel score, thus obtaining the corrected channel score.

[0022] As a further limitation of the technical solution of this embodiment of the invention, the preset channel scoring value correction formula is as follows: ,in This refers to the corrected channel score. This refers to the basic channel score. This refers to the current structural complexity level value. This refers to the structural complexity level value corresponding to the running record of the matching segment. This refers to the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment. This refers to the adjustment coefficient corresponding to the magnitude of the grade deviation.

[0023] A wireless network device configuration system, the system comprising: a data acquisition module, a structure information parsing module, a historical record parsing module, and a score value correction module, wherein:

[0024] The data acquisition module is used to acquire the basic channel score value of the channel to be allocated to the terminal to be configured, which originates from the signal node to which it belongs, and to acquire the historical operation record of the signal node and the tunnel structure information of the tunnel structure to which it belongs.

[0025] The structural information parsing module is used to parse tunnel structural information, determine the first and second identification areas of the terminal to be configured and the signal node, and determine the current structural complexity level value based on the spacing path structure between the first and second identification areas.

[0026] The historical record parsing module is used to parse historical operation records, extract several segment operation records of the channel to be allocated under different structural complexity levels, parse each segment operation record in turn, and determine the matching segment operation record with the data retransmission rate at the middle quantile level.

[0027] The score correction module is used to calculate the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment, and to correct the basic channel score value according to the level deviation.

[0028] As a further limitation of the technical solution of this embodiment of the invention, the structural information parsing module specifically includes:

[0029] The location information acquisition unit is used to acquire the location information of the terminal to be configured and the signal node;

[0030] The path structure acquisition unit is used to parse tunnel structure information, determine the first and second identification areas corresponding to the location information of the terminal to be configured and the signal node, respectively, and acquire the path structure between the first and second identification areas.

[0031] The structural complexity determination unit is used to call a preset reference model to match the spacing path structure in order to determine the current structural complexity level value. The preset reference model is a comparison model used to establish a one-to-one correspondence between the tunnel path structure and the structural complexity level. The preset reference model includes structural complexity level values ​​corresponding to different path lengths, number of path turns, wall material types, metal coverage ratio of the area traversed by the path, number and distribution density of signal blockages, and number of intersecting pipelines.

[0032] As a further limitation of the technical solution of this embodiment of the invention, the historical record parsing module specifically includes:

[0033] The segment operation record acquisition unit is used to parse historical operation records and extract several segment operation records of the channel to be allocated under various structural complexity levels from low to high.

[0034] The data retransmission rate determination unit is used to sequentially parse the operation record of each segment and determine the data retransmission rate of the channel to be allocated within a preset time period.

[0035] The data retransmission rate comparison unit is used to compare data retransmission rates and identify the matching segment operation records at the middle quantile level.

[0036] As a further limitation of the technical solution of this embodiment of the invention, the scoring value correction module specifically includes:

[0037] The correction factor determination unit is used to calculate the magnitude of the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching section, and use it as the correction factor.

[0038] The channel score correction unit is used to call the preset channel score correction formula, substitute the correction factor into the formula, correct the basic channel score, and obtain the corrected channel score.

[0039] The preset channel score correction formula is as follows: ,in This refers to the corrected channel score. This refers to the basic channel score. This refers to the current structural complexity level value. This refers to the structural complexity level value corresponding to the running record of the matching segment. This refers to the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment. This refers to the adjustment coefficient corresponding to the magnitude of the grade deviation.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] This invention dynamically identifies the current structural complexity level by combining the structural path characteristics between the terminal to be configured and the signal node. Using the representative data retransmission rate from historical operation records as a reference, it constructs a level deviation range to correct the basic channel score, thereby achieving dynamic optimization of the channel scoring results. This method effectively solves the problem that traditional channel scoring methods do not consider structural environment differences, avoids communication quality degradation caused by inaccurate scoring, and significantly improves the configuration accuracy and operational stability of wireless network equipment in complex tunnel structures. Attached Figure Description

[0042] Figure 1 A flowchart of the method provided in the embodiments of the present invention;

[0043] Figure 2 This is a flowchart illustrating the method for determining the current structural complexity level value provided in this embodiment of the invention;

[0044] Figure 3 This is a flowchart illustrating the process of finding matching segment operation records in the method provided in this embodiment of the invention;

[0045] Figure 4 This is a flowchart illustrating the correction of the basic channel score value in the method provided in this embodiment of the invention;

[0046] Figure 5Application architecture diagram of the system provided in the embodiments of the present invention;

[0047] Figure 6 This is a structural block diagram of the structural information parsing module in the system provided in the embodiments of the present invention;

[0048] Figure 7 This is a structural block diagram of the historical record parsing module in the system provided in the embodiments of the present invention;

[0049] Figure 8 This is a structural block diagram of the scoring value correction module in the system provided in the embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0052] Specifically, a method for configuring a wireless network device includes the following steps:

[0053] Step S100: Obtain the basic channel score value of the channel to be allocated to the terminal to be configured, which originates from the signal node to which it belongs, and at the same time obtain the historical operation record of the signal node and the tunnel structure information of the tunnel structure to which it belongs.

[0054] In this embodiment of the invention, the wireless network device configuration method is applicable to tunnel scenarios, including but not limited to communication deployment needs in closed or semi-closed environments such as subway construction tunnels, highway tunnels, power tunnels, and utility tunnels. The terminal to be configured can be various communication terminal devices deployed within the tunnel structure that need to access the wireless network system, such as mobile construction monitoring terminals, environmental sensor nodes, image acquisition modules, wireless data repeaters, emergency contact terminals, mobile robot terminals, or other devices with wireless communication capabilities.

[0055] A signal node refers to a network node device deployed within a tunnel structure that possesses wireless signal transmission and communication scheduling capabilities. It can function as a signal source in the network, such as a tunnel master AP (access point), edge gateway device, or wireless relay base station. A channel to be allocated refers to a wireless communication channel that the signal node can currently use to provide communication connections to target terminals. Examples include a specific frequency band channel in a WiFi network, a channel number or frequency resource point under IoT protocols such as 5G / LoRa, and the specific type can be selected according to the wireless communication protocol.

[0056] The basic channel score is a reference value generated by the system based on the target signal node for the channel to be assigned under the current environment. This score characterizes the communication quality, stability, and interference of the channel. This score can be generated using widely used channel evaluation methods in existing technologies. For example, it comprehensively considers factors such as the channel's real-time RSSI (Received Signal Strength Indicator), SNR (Signal-to-Noise Ratio), current connection count, historical congestion, packet loss rate, and spectral interference intensity within the target area, and outputs a numerical score result through mechanisms such as linear weighting, neural network fitting, or rule matching. Such channel scoring mechanisms are commonly found in existing communication systems and are frequently used in dynamic channel selection, automatic frequency hopping decisions, and load balancing scheduling.

[0057] The historical operation record of a signal node refers to the operational data log recorded by the signal node within a preset historical period. This includes, but is not limited to, signal transmission performance data for different channels under different structural complexity environments, such as channel usage status, historical data retransmission rate, instantaneous throughput, connection stability, and interference event records. Tunnel structure information refers to the data set within the tunnel structure to which the signal node belongs, used to describe the path's structural characteristics. Tunnel structure information can be obtained by parsing BIM information or other structural drawings of the tunnel structure. BIM information contains construction details of the tunnel structure in different spatial areas, providing parameters related to signal propagation such as path length, number of path turns, wall material type, metal coverage ratio of the areas traversed by the path, number and distribution density of signal obstructions, number of intersecting pipelines, and location information corresponding to different areas.

[0058] Furthermore, the wireless network device configuration method further includes the following steps:

[0059] Step S200: Analyze the tunnel structure information, determine the first and second identification areas of the terminal to be configured and the signal node, and determine the current structure complexity level value based on the spacing path structure between the first and second identification areas.

[0060] Specifically, Figure 2 A flowchart is shown to determine the current structural complexity level value.

[0061] The process of parsing tunnel structure information, determining the first and second identification regions of the terminal to be configured and the signal node, and determining the current structural complexity level based on the path structure between the first and second identification regions includes the following steps:

[0062] Step S201: Obtain the location information of the terminal to be configured and the signal node;

[0063] Step S202: parse the tunnel structure information, determine the first and second identification areas corresponding to the location information of the terminal to be configured and the signal node respectively, and obtain the spacing path structure between the first and second identification areas;

[0064] Step S203: Call the preset reference model to match the spacing path structure in order to determine the current structural complexity level value.

[0065] The preset reference model is a comparative model used to establish a one-to-one correspondence between tunnel path structure and structural complexity level. The preset reference model includes structural complexity level values ​​corresponding to different path lengths, number of path turns, wall material types, metal coverage ratio of the area traversed by the path, number and distribution density of signal blockages, and number of intersecting pipelines.

[0066] In this embodiment of the invention, the location information of the terminal to be configured and the signal node can be obtained through various existing technical means. Specifically, when the terminal to be configured is a mobile device, its location information can be obtained through an inertial navigation system, ultra-wideband positioning (UWB), Bluetooth AoA positioning, WiFi RSSI positioning, or the BeiDou / GPS system; when the terminal to be configured is a fixed device, its location information can be directly marked and stored in the management system during the device installation phase through a BIM modeling system, digital map, or construction drawings. As a fixed communication facility in the network structure, the location information of the signal node is usually preset in the network management system during the system deployment phase and can be directly accessed.

[0067] In practical applications, after obtaining the location information of the terminal to be configured and the signal node, the system can project them onto the corresponding tunnel structure model. The process of parsing the tunnel structure information is preferably based on BIM data or a digital 3D tunnel model. BIM information contains structural labels, spatial topological relationships, and construction parameters for each area of ​​the tunnel. By calling the location information and the spatial division rules in the BIM model, the first and second identification areas corresponding to the terminal to be configured and the signal node can be located respectively.

[0068] The process of obtaining the spacing path structure between the first and second identification areas includes: extracting the shortest or preset propagation path between the first and second identification areas based on the tunnel's three-dimensional structural model, traversing all structural segments along the path, and extracting the path length, turning position, wall type, metal coverage, distribution of obstructions, and information on intersecting components for each structural segment, thereby forming the spacing path structure.

[0069] The preset reference model is a structural mapping model used to establish a one-to-one correspondence between tunnel path structure and structural complexity level. The model can output a unique structural complexity level value based on different combinations of path structure parameters. The reference model can be established based on one or a combination of the following two methods:

[0070] On the one hand, it can be constructed using an expert experience model based on rule settings. This involves combining existing tunnel signal propagation principles and engineering experience to set weights for the influence of several path structure parameters (including path length, number of path turns, wall material type, metal coverage ratio, number and density of signal blockages, and number of intersecting pipelines) on signal propagation complexity. By constructing a rule matrix or a polynomial scoring function, these parameters are input into the corresponding formula for weighted scoring, ultimately dividing the scoring results into several structural complexity level intervals, with each combination corresponding to a unique level value.

[0071] On the other hand, a data-driven approach can also be used. This involves collecting historical propagation performance and structural parameter data samples from different types of tunnel environments, and then using regression analysis, clustering algorithms, or lightweight neural networks for model training and classification. This results in a model system capable of automatically determining the level of structural complexity based on actual path structural characteristics. This method possesses a degree of adaptability, allowing for continuous optimization of model accuracy as the data scales.

[0072] The aforementioned preset reference model can be constructed using the structural feature extraction and rating module integrated into existing tunnel BIM systems, communication simulation platforms (such as WirelessInSite), or communication network deployment software.

[0073] Furthermore, the wireless network device configuration method further includes the following steps:

[0074] Step S300: parse the historical operation records, extract several segment operation records of the channel to be allocated under different structural complexity levels, parse each segment operation record in turn, and determine the matching segment operation record with the data retransmission rate at the middle quantile level.

[0075] Specifically, Figure 3 A flowchart is shown to find the running records of the matching segment.

[0076] The process of parsing historical operation records, extracting several segment operation records of the channel to be allocated under different structural complexity levels, and then parsing each segment operation record sequentially to determine the matching segment operation record with a data retransmission rate at the middle quantile level specifically includes the following steps:

[0077] Step S301: parse the historical operation records and extract the operation records of several segments of the channel to be allocated under each structural complexity level value from low to high;

[0078] Step S302: Analyze the operation record of each segment in sequence to determine the data retransmission rate of the channel to be allocated within the preset time period;

[0079] Step S303: Compare the data retransmission rates and identify the matching segment operation records at the middle quantile level.

[0080] In this embodiment of the invention, step S301 includes the following process: Based on the historical operation records of the signal nodes, all data items that use the channel to be allocated for communication in all records are filtered out, and the structural complexity level labeling information in the historical records is combined to classify and organize different level intervals. The structural complexity level values ​​can correspond one-to-one with the hierarchical system in the preset reference model. For each level interval, multiple communication path segments that actually exist under that level are further identified, and the corresponding operation records are extracted to form several segment operation record sets. Each segment operation record includes channel number, path structure identifier, timestamp, and channel operation performance data, etc.

[0081] The preset time period refers to the length of the historical interval used for statistical analysis of data retransmission rates. Its setting can be configured based on the network system's requirements for extracting historical performance characteristics, combined with the complexity of the scenario and the frequency of device operation. For example, for terminals with high daily operating frequency, records from the past 1 or 3 days can be selected; for devices operating intermittently, a longer period such as 7 or 30 days can be set to ensure the representativeness and stability of the sample data. The preset time period can be a fixed time window or a sliding time window based on the number of communications.

[0082] The data retransmission rate can be obtained by parsing the communication log field in each segment's operation record. This field records the data packet transmission status between the signal node and the terminal within a preset time period, including the total number of successfully sent data packets and the number of data packets actually received and acknowledged. The data retransmission rate is calculated based on the ratio of the cumulative number of retransmission events to the total number of transmissions, reflecting the stability level of the communication link under this path structure.

[0083] Identifying matching segments at the median quantile level aims to select representative data samples for comparison, thereby avoiding bias caused by using extreme data. Directly selecting the records with the lowest or highest retransmission rates might lead to evaluation results lacking universality due to occasional external factors. Selecting records at the median quantile level better reflects the typical performance of the channel to be assigned at that complexity level, making subsequent scoring adjustments based on these records more stable and scientific. Furthermore, using data at the median quantile level reduces the risk of being affected by abnormal interference values, improving the adaptability of the evaluation results to complex structural environments.

[0084] Indicators used to characterize channel operational stability include not only data retransmission rate, but also other representative data performance indicators that can be selected according to specific application requirements, including but not limited to average round-trip time, packet loss rate, connection interruption frequency, number of ACK confirmation failures, throughput rate fluctuation, and signal-to-noise ratio fluctuation. All of the above indicators can be extracted from historical operation records and can reflect the communication reliability and link stability of the channel to be allocated at a specific structural complexity level from different perspectives. They can be used to replace or supplement the data retransmission rate to construct the screening criteria for matching segment operation records.

[0085] Furthermore, the wireless network device configuration method further includes the following steps:

[0086] Step S400: Calculate the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the matching segment operation record, and correct the basic channel score value according to the level deviation.

[0087] Specifically, Figure 4 A flowchart illustrating the correction of the base channel score is shown.

[0088] The calculation of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the matching segment's operational record, and the correction of the basic channel score value based on the deviation, specifically includes the following steps:

[0089] Step S401: Calculate the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching section, and use it as a correction factor;

[0090] Step S402: Call the preset channel score correction formula, substitute the correction factor into the formula, correct the basic channel score, and obtain the corrected channel score.

[0091] The preset channel score correction formula is as follows: ,in This refers to the corrected channel score. This refers to the basic channel score. This refers to the current structural complexity level value. This refers to the structural complexity level value corresponding to the running record of the matching segment. This refers to the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment. This refers to the adjustment coefficient corresponding to the magnitude of the grade deviation.

[0092] In this embodiment of the invention, by calculating the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the matching segment's operational record, and using this deviation as a correction factor to adjust the basic channel score value, the scientific validity and adaptability of the channel scoring results in tunnel-like scenarios can be effectively improved. The core significance of this step lies in the fact that the current structural complexity level value reflects the complexity of the propagation environment of the actual path of the target device, while the structural complexity level value corresponding to the matching segment's operational record is a relatively stable reference value from historical operational data. If there is a large difference between the two, it means that directly using the basic channel score value may underestimate or overestimate the channel's true performance in the current path. By introducing the magnitude of the deviation as a correction factor, the channel scoring results can be transformed from static estimation to dynamic adaptation, thereby solving the problem that traditional scoring methods fail to fully reflect the changes in signal propagation complexity caused by structural path differences, and avoiding connection instability or communication quality degradation caused by inaccurate channel selection.

[0093] In this embodiment, as described in the formula above, the channel score is corrected using a proportional factor weighted adjustment method based on the magnitude of the grade deviation. Specifically, the base channel score is multiplied by a correction term, which is calculated from the relative difference between the grade deviation value and the reference grade value, and an adjustment coefficient is introduced as a control parameter for the adjustment magnitude. This correction formula is an illustrative expression used to illustrate the direct impact of grade deviation on the channel score. In practical applications, other forms of correction calculation methods can also be used, such as exponential decay methods, polynomial offset functions, neural network regression models, and nonlinear interpolation mechanisms between grades, to flexibly select the optimal score adjustment method based on the system deployment scenario, sample training results, or security redundancy requirements.

[0094] In summary, the wireless network device configuration method provided by this invention can dynamically correct and finely evaluate channel scores in complex environments such as tunnels. It fully combines the structural complexity level information of the target device's current path with the comparison results of representative stable operating samples in historical operating data to establish a correction factor. Through a scoring adjustment mechanism, it improves the accuracy and adaptability of channel selection. This solves the problem in the prior art where the channel scoring mechanism only relies on real-time signal parameters and ignores the influence of structural path differences, leading to inaccurate channel selection, unstable network connection, or communication quality fluctuations. It significantly improves the configuration efficiency and communication stability of wireless network devices in complex structural scenarios, and has good engineering practical value and promotion prospects.

[0095] Furthermore, Figure 5 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0096] In another preferred embodiment of the present invention, a wireless network device configuration system includes:

[0097] The data acquisition module 100 is used to acquire the basic channel score value of the channel to be allocated to the terminal to be configured, which originates from the signal node to which it belongs, and to acquire the historical operation record of the signal node and the tunnel structure information of the tunnel structure to which it belongs.

[0098] Furthermore, the wireless network device configuration system also includes:

[0099] The structural information parsing module 200 is used to parse tunnel structural information, determine the first and second identification areas of the terminal to be configured and the signal node, and determine the current structural complexity level value based on the spacing path structure between the first and second identification areas.

[0100] Specifically, Figure 6 A structural block diagram of the structural information parsing module 200 in the system provided in an embodiment of the present invention is shown.

[0101] In a preferred embodiment provided by the present invention, the structural information parsing module 200 specifically includes:

[0102] Location information acquisition unit 201 is used to acquire the location information of the terminal to be configured and the signal node;

[0103] The path structure acquisition unit 202 is used to parse the tunnel structure information, determine the first identification area and the second identification area corresponding to the location information of the terminal to be configured and the signal node respectively, and acquire the spacing path structure between the first identification area and the second identification area.

[0104] The structural complexity determination unit 203 is used to call a preset reference model to match the spacing path structure in order to determine the current structural complexity level value. The preset reference model is a comparison model used to establish a one-to-one correspondence between the tunnel path structure and the structural complexity level. The preset reference model includes structural complexity level values ​​corresponding to different path lengths, number of path turns, wall material types, metal coverage ratio of the area traversed by the path, number and distribution density of signal blockages, and number of intersecting pipelines.

[0105] Furthermore, the wireless network device configuration system also includes:

[0106] The historical record parsing module 300 is used to parse historical operation records, extract several segment operation records of the channel to be allocated under different structural complexity levels, parse each segment operation record in turn, and determine the matching segment operation record whose data retransmission rate is at the middle quantile level.

[0107] Specifically, Figure 7 A structural block diagram of the historical record parsing module 300 in the system provided by an embodiment of the present invention is shown.

[0108] In a preferred embodiment provided by the present invention, the historical record parsing module 300 specifically includes:

[0109] The segment operation record acquisition unit 301 is used to parse historical operation records and extract several segment operation records of the channel to be allocated under each structural complexity level value from low to high.

[0110] The data retransmission rate determination unit 302 is used to sequentially parse the operation record of each segment and determine the data retransmission rate of the channel to be allocated within a preset time period.

[0111] The data retransmission rate comparison unit 303 is used to compare the data retransmission rates and identify the running records of the matching segment at the middle percentile level.

[0112] Furthermore, the wireless network device configuration system also includes:

[0113] The scoring value correction module 400 is used to calculate the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment, and to correct the basic channel scoring value according to the level deviation.

[0114] Specifically, Figure 8 A structural block diagram of the scoring value correction module 400 in the system provided in an embodiment of the present invention is shown.

[0115] In a preferred embodiment of the present invention, the scoring value correction module 400 specifically includes:

[0116] The correction factor determination unit 401 is used to calculate the magnitude of the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching section, and use it as the correction factor.

[0117] The channel score correction unit 402 is used to call a preset channel score correction formula, substitute the correction factor into the formula, correct the basic channel score, and obtain the corrected channel score.

[0118] The preset channel score correction formula is as follows: ,in This refers to the corrected channel score. This refers to the basic channel score. This refers to the current structural complexity level value. This refers to the structural complexity level value corresponding to the running record of the matching segment. This refers to the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment. This refers to the adjustment coefficient corresponding to the magnitude of the grade deviation.

[0119] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0120] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0121] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0122] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0123] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for configuring a wireless network device, characterized in that, The method includes: Obtain the basic channel score value of the channel to be allocated to the terminal to be configured, which originates from the signal node to which it belongs, and at the same time obtain the historical operation record of the signal node and the tunnel structure information of the tunnel structure to which it belongs; The tunnel structure information is analyzed to determine the first and second identification areas of the terminal to be configured and the signal node, respectively. Based on the spacing path structure between the first and second identification areas, the current structural complexity level value is determined. Analyze historical operation records, extract several segment operation records of the channel to be allocated under different structural complexity levels, analyze each segment operation record in turn, and determine the matching segment operation record with the data retransmission rate at the middle percentile level. Calculate the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment, and correct the basic channel score value based on the deviation.

2. The wireless network device configuration method according to claim 1, characterized in that, The steps for analyzing tunnel structure information, determining the first and second identification regions of the terminal to be configured and the signal node, and determining the current structural complexity level based on the path structure between the first and second identification regions include: Obtain the location information of the terminal to be configured and the signal node; The tunnel structure information is analyzed to determine the first and second identification areas corresponding to the location information of the terminal to be configured and the signal node, respectively, and the spacing path structure between the first and second identification areas is obtained. The preset reference model is invoked to match the spacing path structure in order to determine the current structural complexity level value.

3. The wireless network device configuration method according to claim 2, characterized in that, The preset reference model is a comparative model used to establish a one-to-one correspondence between tunnel path structure and structural complexity level value. The preset reference model includes structural complexity level values ​​corresponding to different path lengths, number of path turns, wall material types, metal coverage ratio of the area traversed by the path, number and distribution density of signal blockages, and number of intersecting pipelines.

4. The wireless network device configuration method according to claim 1, characterized in that, The steps of parsing historical operation records, extracting several segment operation records of the channel to be allocated under different structural complexity levels, and sequentially parsing each segment operation record to determine the matching segment operation record with a data retransmission rate at the middle quantile level include: Analyze historical operation records to extract the operation records of several segments of the channel to be allocated under various structural complexity levels from low to high; The operation record of each segment is analyzed sequentially to determine the data retransmission rate of the channel to be allocated within a preset time period. By comparing the data retransmission rates, the matching segment operation records at the middle quantile level are identified.

5. The wireless network device configuration method according to claim 1, characterized in that, The steps for calculating the deviation between the current structural complexity level and the structural complexity level corresponding to the matching segment's operational record, and for correcting the base channel score based on the deviation, include: Calculate the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching section, and use it as a correction factor; The preset channel score correction formula is invoked, and the correction factor is substituted into the formula to correct the basic channel score, thus obtaining the corrected channel score.

6. The wireless network device configuration method according to claim 5, characterized in that, The preset channel score correction formula is as follows: ,in This refers to the corrected channel score. This refers to the basic channel score. This refers to the current structural complexity level value. This refers to the structural complexity level value corresponding to the running record of the matching segment. This refers to the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment. This refers to the adjustment coefficient corresponding to the magnitude of the grade deviation.

7. A wireless network device configuration system, characterized in that, The system includes: a data acquisition module, a structural information parsing module, a historical record parsing module, and a score correction module, wherein: The data acquisition module is used to acquire the basic channel score value of the channel to be allocated to the terminal to be configured, which originates from the signal node to which it belongs, and to acquire the historical operation record of the signal node and the tunnel structure information of the tunnel structure to which it belongs. The structural information parsing module is used to parse tunnel structural information, determine the first and second identification areas of the terminal to be configured and the signal node, and determine the current structural complexity level value based on the spacing path structure between the first and second identification areas. The historical record parsing module is used to parse historical operation records, extract several segment operation records of the channel to be allocated under different structural complexity levels, parse each segment operation record in turn, and determine the matching segment operation record with the data retransmission rate at the middle quantile level. The score correction module is used to calculate the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment, and to correct the basic channel score value according to the level deviation.

8. The wireless network device configuration system according to claim 7, characterized in that, The structural information parsing module specifically includes: The location information acquisition unit is used to acquire the location information of the terminal to be configured and the signal node; The path structure acquisition unit is used to parse tunnel structure information, determine the first and second identification areas corresponding to the location information of the terminal to be configured and the signal node, respectively, and acquire the path structure between the first and second identification areas. The structural complexity determination unit is used to call a preset reference model to match the spacing path structure in order to determine the current structural complexity level value. The preset reference model is a comparison model used to establish a one-to-one correspondence between the tunnel path structure and the structural complexity level value. The preset reference model includes the structural complexity level values ​​corresponding to different path lengths, number of path turns, wall material types, metal coverage ratio of the area traversed by the path, number and distribution density of signal blockages, and number of intersecting pipelines.

9. The wireless network device configuration system according to claim 8, characterized in that, The historical record parsing module specifically includes: The segment operation record acquisition unit is used to parse historical operation records and extract several segment operation records of the channel to be allocated under various structural complexity levels from low to high. The data retransmission rate determination unit is used to sequentially parse the operation record of each segment and determine the data retransmission rate of the channel to be allocated within a preset time period. The data retransmission rate comparison unit is used to compare data retransmission rates and identify the matching segment operation records at the middle quantile level.

10. The wireless network device configuration system according to claim 9, characterized in that, The scoring value correction module specifically includes: The correction factor determination unit is used to calculate the magnitude of the level deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching section, and use it as the correction factor. The channel score correction unit is used to call the preset channel score correction formula, substitute the correction factor into the formula, correct the basic channel score, and obtain the corrected channel score. The preset channel score correction formula is as follows: ,in This refers to the corrected channel score. This refers to the basic channel score. This refers to the current structural complexity level value. This refers to the structural complexity level value corresponding to the running record of the matching segment. This refers to the magnitude of the deviation between the current structural complexity level value and the structural complexity level value corresponding to the running record of the matching segment. This refers to the adjustment coefficient corresponding to the magnitude of the grade deviation.

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