A base station performance analysis method and system

A base station performance analysis method and system technical field

[0001] The present invention relates to the field of mobile communication technology and big data analysis and processing technology, and in particular, to a method and system for base station performance analysis.

Background technique

[0002] In recent years, with the advent of the rapid development of the Internet, modern people's lives have long been inseparable from mobile communications. In real life, the emergency communication capability of the communication network also presents its indispensable and important position in emergency rescue work. In order to obtain the abnormal activities reflected by the emergency network while the emergency communication system is operating stably, it is necessary to simulate the signal coverage of the emergency network base station and evaluate the performance of the affected base station, so that the relevant departments can quickly and effectively emergency procedures. Therefore, designing a system that can dynamically simulate the signal coverage of the base station of the emergency communication network, and can timely evaluate the performance of the indicators of the affected base station has important practical significance for the relevant departments to formulate emergency plans.

[0003] Emergency communication provides timely and effective communication guarantee for various emergencies. It is an important part of the comprehensive application guarantee system, and it is also the lifeline of emergency rescue and disaster relief. Internationally, many countries attach great importance to the research and development of emergency communication networks. The United States began to establish emergency communication networks in the 1970s to meet the command and dispatch requirements of the US government for emergencies. It also invested heavily in the construction of a government private network physically separated from the Internet, implemented a limited communications service plan, and used free space optical communications, WIMAX, WI-FI and other technologies to improve emergency communications support capabilities. Although my country's emergency communication guarantee system has made great progress, there are still problems such as backward technical system and insufficient capital investment, which is far from the actual requirements of emergency communication.

[0004] In order to be able to reflect the abnormalities of the communication network in time and take corresponding remedial measures, local governments have established their own emergency communication network systems in accordance with their own geographic locations and economic conditions. At present, most emergency response plans of emergency communication network systems are designed based on the network topology of the system itself. These systems are mainly a series of rule bases established by experts who are familiar with communication business knowledge and have experience in data analysis. The rules of this type of emergency communication system are generally relatively simple. It only needs to judge whether the base station is abnormal based on whether the link in the network topology is interrupted, and it does not reflect the strength or weakness of the signal within the coverage of the emergency network base station. There is no signal, and the load capacity of all base stations in the entire system cannot be reflected.

Summary of the invention

[0005] In view of this, the purpose of the embodiments of the present invention is to provide a base station performance analysis method and device to solve the above technical problems.

[0006] In the first aspect, an embodiment of the present invention provides a base station performance analysis method, including:

[0007] Obtain status data of all base stations in the communication system corresponding to the area to be tested, where the status data includes base station node parameters, system environment parameters, and network topology information;

[0008] Perform dynamic simulation based on the base station node parameters, system environment parameters, and network topology information to obtain a signal coverage map corresponding to the area to be tested, and identify signal blind areas based on the signal coverage map; and

[0009] Perform base station performance evaluation according to the base station node parameters, system environment parameters, and network topology information to obtain

Operation status information corresponding to each base station in the area to be tested.

[0010] Further, the dynamic simulation based on the base station node parameters, system environment parameters and network topology information to obtain the signal coverage map corresponding to the area to be tested includes:

[0011] According to the base station node parameters, system environment parameters and network topology information, the signal overlap method is used to obtain the coverage signal strength corresponding to each cell in the area to be tested;

[0012] The signal coverage map is obtained by plotting points according to the coverage signal strength of each cell.

[0013] Further, the identification of the signal blind area according to the signal coverage map includes:, f0, O<C, <127

[0014] Perform binarization processing on the signal coverage map according to two to obtain a binarized image, mouth, C_nm > 127

C_mnIs the pixel value of the pixel corresponding to the mth row and the nth column in the signal coverage map, C'_mn*The gray value of the pixel corresponding to the mth row and the nth column in the binarized image;

()('= j

[0015] According to =, perform pixel inversion processing on the binarized image to obtain a flipped image; where (/, is the gray value of the pixel corresponding to the mth row and nth column in the flipped image;

[0016] Perform image filtering, image expansion, image erosion, contour orientation detection, and contour delineation processing on the flipped image to obtain the signal blind zone.

[0017] Further, the performing base station performance evaluation according to the base station node parameters, system environment parameters, and network topology information to obtain operating status information corresponding to each base station in the area to be tested includes:

[0018] According to the base station node parameters, system environment parameters and network topology information, the PageRank algorithm is used to calculate the PageRank score corresponding to each base station, and the operating status information of the corresponding base station is determined according to the PageRank score of each base station.

[0019] Further, the obtaining the coverage signal strength corresponding to each cell in the area to be tested by using the signal overlap method according to the base station node parameters, system environment parameters, and network topology information includes:

[0020] Obtain the signal coverage strength of each cell according to = max{^ h ten calculations;

Q<i<n

[0021] Wherein, signalk is the signal coverage strength corresponding to the k-th cell; C_ikIs the signal coverage strength of the i-th base station to the k-th cell, and i and k are positive integers.

[0022] Further, the calculation of the PageRank score corresponding to each base station by using the PageRank algorithm according to the base station node parameters, system environment parameters and network topology information includes:

[0023] +ί/·V

Ton) Rain Γ calculates the PageRank score corresponding to each base station;

[0024] Wherein, PR (Pi) is the PageRank score corresponding to the Pi base station, C (Pj) is the number of outgoing links of Pj, and Pj is all base stations included in the area to be tested except P and base stations. ; q is the damping coefficient; N is the total number of base stations.

[0025] Further, after determining the operating status information of the corresponding base station according to the PageRank score of each base station, the method further includes:

[0026] If the PageRank score corresponding to the base station is greater than the preset threshold, an alarm is issued.

[0027] Further, the method further includes:

[0028] The signal coverage map, the signal blind area, and the operating status information corresponding to each base station are displayed and stored together

Reserve.

[0029] Further, after acquiring the status data of all base stations in the communication system corresponding to the area to be tested, the method further includes:

[0030] A preprocessing operation is performed on the state data, wherein the preprocessing operation includes any one or a combination of missing processing, outlier processing, data integration, data discretization, and data standardization processing.

[0031] In the second aspect, an embodiment of the present invention provides a base station performance analysis system, including:

[0032] The data collection module is used to obtain status data of all base stations in the communication system corresponding to the area to be tested, the status data including base station node parameters, system environment parameters, and network topology information;

[0033] The simulation module is used to perform dynamic simulation simulation according to the base station node parameters, system environment parameters and network topology information, to obtain the signal coverage map corresponding to the area to be tested, and to identify the signal according to the signal coverage map Blind spot

[0034] The performance evaluation module is configured to perform base station performance evaluation according to the base station node parameters, system environment parameters, and network topology information, and obtain operating status information corresponding to each base station in the area to be tested.

[0035] In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor, a memory, and a bus, where [0036] the processor and the memory complete mutual communication through the bus;

[0037] The memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the method steps of the first aspect.

[0038] In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, including:

[0039] The non-transitory computer-readable storage medium stores computer instructions that cause the computer to perform the method steps of the first aspect.

[0040] In the embodiments of the present invention, by using base station node parameters, system environment parameters, and network topology information to perform simulation simulation and performance evaluation of the base stations in the area to be tested, the corresponding signal coverage map, signal blind zone, and operating status information of each base station are obtained, Therefore, the operating status of the communication system corresponding to the area to be measured can be obtained more accurately.

[0041] Other features and advantages of the present invention will be described later, and partly become obvious from them, or understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings.

Description of the drawings

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings needed in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention. Therefore, it should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative work, other related drawings can be obtained based on these drawings.

[0043] FIG. 1 is a base station performance analysis method provided by an embodiment of the present invention;

[0044] FIG. 2 is a schematic diagram of a dynamic simulation simulation process provided by an embodiment of the present invention;

[0045] FIG. 3 is a schematic diagram of a base station evaluation process provided by an embodiment of the present invention;

[0046] FIG. 4 is a schematic structural diagram of a base station performance analysis system provided by an embodiment of the present invention;

[0047] FIG. 5 is a schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention.

Detailed ways

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. . The components of the embodiments of the present invention generally described and illustrated in the drawings herein may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the protection scope of the present invention.

[0049] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined in subsequent drawings. And explanation. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. [0050] FIG. 1 is a base station performance analysis method provided by an embodiment of the present invention. As shown in FIG. 1, the method includes:

[0051] Step 101: Obtain status data of all base stations in the communication system corresponding to the area to be tested, where the status data includes base station node parameters, system environment parameters, and network topology information.

[0052] In a specific implementation process, the analysis system can be connected to the communication system through a data collection interface, and then through the data collection interface to obtain the status data of all base stations in the area to be tested, it should be noted that the analysis system obtains the status data in real time , And store the status data. Therefore, both historical status data and current status data are stored in the analysis system. Among them, the communication system may be an emergency communication network system, and the status data may include base station node parameters, system environment parameters, and network topology information of the communication system, as well as signal coverage data, base station communication data, and user behavior data within the system. Wait. In addition, the network topology information includes information such as the number, latitude and longitude of the base station, the number of resident population of the base station, the type of area where the base station is located, and the capacity of the base station service channel.

[0053] Step 102: Perform dynamic simulation based on the base station node parameters, system environment parameters, and network topology information to obtain a signal coverage map corresponding to the area to be tested, and identify signal blind areas based on the signal coverage map.

[0054] In a specific implementation process, the network topology information includes the base station number, latitude and longitude, the number of permanent population of the base station, the type of base station location, base station service channel capacity and other information. The base station node parameters include road measurement signals, and the system environment parameters include Base station coverage data, etc. After the analysis system obtains the status data, it performs dynamic simulation based on the base station number, latitude and longitude, the number of permanent population of the base station, the type of the base station, the capacity of the base station service channel, and other information, road measurement signals and base station coverage data, so-called dynamic simulation. Simulation is because the analysis system will obtain the status data in real time, and after the new status data is acquired, the corresponding simulation simulation will be carried out, so it is called dynamic simulation simulation. After dynamic simulation, the coverage signal strength of each cell in the area to be tested can be obtained, the signal coverage map is drawn and generated according to the coverage signal strength, and the signal blind area is identified according to the signal coverage map. It is understandable that the area to be tested may include multiple cells, and when the communication system is operating normally, each cell has at least one base station to cover it.

[0055] Step 103: Perform base station performance evaluation according to the base station node parameters, system environment parameters, and network topology information, and obtain operating status information corresponding to each base station in the area to be tested.

[0056] On the basis of the foregoing embodiment, after the analysis system obtains the status data, the performance of each base station in the area to be tested is evaluated according to the base station node parameters, system environment parameters, and network topology information, and the operation of each base station is obtained. status information. It is understandable that the operating status information may include the load capacity of each base station.

[0057] It should be noted that when evaluating the performance of a base station, the required parameters may specifically include: the network topology of the base station in the network topology information, the number of real-time login personnel of the base station in the system environment parameters, and the base station node In the parameter, the real-time service channel capacity of the base station and the real-time service channel occupation ratio of the base station. Step 102 and step 103 can be

It can be carried out in parallel or one after the other, and the sequence can be adjusted according to the actual situation.

[0058] The embodiment of the present invention uses base station node parameters, system environment parameters, and network topology information to perform simulation simulation and performance evaluation of base stations in the area to be tested to obtain corresponding signal coverage maps, signal blind areas, and operating status information of each base station, Thereby, the operating status of the communication system corresponding to the area to be measured can be obtained more accurately.

[0059] On the basis of the foregoing embodiment, the dynamic simulation based on the base station node parameters, system environment parameters and network topology information to obtain the signal coverage map corresponding to the area to be tested includes:

[0060] According to the base station node parameters, system environment parameters and network topology information, the signal overlap method is used to obtain the coverage signal strength corresponding to each cell in the area to be tested;

[00611 Plotting points according to the coverage signal strength of each cell to obtain the signal coverage map.

[0062] In a specific implementation process, FIG. 2 is a schematic diagram of a dynamic simulation simulation process provided by an embodiment of the present invention. As shown in FIG. 2, the process mainly includes:

[0063] Step 201: Data conversion; the format of the state data obtained by the analysis system is not uniform, and the data format required for dynamic simulation is different from the format of the state data obtained by the analysis system. Therefore, before performing dynamic simulation, you can Data conversion is performed on the status data obtained by the analysis system, and the format of the status data is converted into a format that meets the needs.

[0064] Step 202: signal dynamic simulation; in the process of dynamic simulation simulation, the signal overlap method can be used to analyze the coverage of each cell by the base station.

[0065] The specific simulation process is as follows:

[0066] Assume that C₂, C₃, C₄···. CJ is the signal coverage information of m base stations. It should be noted that the value of m is determined by the number of base stations in the area to be tested. The structure of the entire data field should be:

<td>[0067]</td><td>{Cll, Cl2, Cl3, Cl4····</td><td> Cln}</td>

<td>[0068]</td><td>{C21, C22, C23, C24····</td><td> C_2n}</td>

<td>[0069]</td><td>{¢31,632,633,634---</td><td> · C3n}</td>

<td>[0070]</td><td></td><td></td>

<td>[0071]</td><td>{Cml, Cm2, Cm3, Cm4· · · ·</td><td>.Cmn}</td>

[0072] where C₁₂The meaning of is that the first base station corresponds to the particle signal of the second cell at the current moment. The entire data set has n data fields, which simply describes the data form required for this process.

[0073] Calculate the signal coverage strength of each cell according to "X=max{Q];

[0074] Wherein, signalk is the signal coverage strength corresponding to the k-th cell; and the k-th cell is covered by signals by at least one base station, C_lkIs the signal coverage strength of the i-th base station to the k-th cell, and C_lkThe value of can be obtained by analyzing the base station node parameters, system environment parameters and network topology information obtained by the system, i and k are positive integers, the maximum value of k is determined by the number of base stations included in the area to be tested, and the maximum value of η is determined by The total number of base stations covered by the cell to be calculated is determined. For example: when calculating the signal coverage strength of a certain cell, suppose there are three base stations covering the cell at the same time, then η is 3, each base station has a corresponding signal coverage strength for the cell, and the one with the largest signal coverage strength is taken as the The signal coverage strength of the cell.

[0075] Step 203: Generate a signal coverage map; after obtaining the signal coverage intensity corresponding to each cell, trace points in the form of a scatter diagram to generate a signal coverage map, and identify the current signal blind area for the signal coverage map. It is understandable that the area that is not covered by the signal in the signal coverage map is called the signal dead zone. Understandably, each dot represents

A cell can express the signal coverage strength through different colors or different color depths. It can be that the stronger the signal coverage strength, the darker the color of the traced point, and the signal coverage strength value can be directly marked on the corresponding point.

[0076] The embodiment of the present invention obtains the signal coverage map corresponding to the area to be tested according to the coverage signal strength corresponding to each cell, so that the signal coverage of each cell in the area to be tested can be obtained more intuitively.

[0077] On the basis of the foregoing embodiment, the identifying the signal blind area according to the signal coverage map includes:

[0078] Step 204: Image binarization; after obtaining the signal coverage map corresponding to the area to be tested, according to

Γ0 0 &lt;C &lt;127

C- /, two pairs of signal coverage maps are binarized to obtain a binarized image, C_mnIs the signal coverage map

I¹，>¹²⁷ The pixel value of the pixel corresponding to the mth row and the nth column, C'_mnIs the gray value of the pixel corresponding to the mth row and the nth column in the binarized image; fo C'=1

[0079] Step 205: Image pixel inversion; according to: pixel inversion processing is performed on the binarized image to obtain a flipped image; where C'_m’_nIs the gray value of the pixel corresponding to the m-th row and the n-th column in the flipped image;

[0080] Step 206: image contour detection; performing image filtering, image expansion, image erosion, contour orientation detection, and contour delineation processing on the flipped image to obtain the signal blind area.

[0081] Image filtering technology mainly removes some noise (such as Gaussian white noise) in the image. Expansion is to expand the highlighted part of the image, "neighborhood expansion", the effect picture has a larger highlight area than the original image. Corrosion means that the highlighted part of the original image is corroded, "neighborhood is eroded", and the effect image has a smaller highlight area than the original image. In this process, the image filtering process, the image expansion process, and the image corrosion process are alternately performed many times. How many times the process needs to be performed can be determined according to the accuracy requirements and the actual production method.

[0082] Image filtering processing technologies include but are not limited to the following technologies:

[00⁸³] 1) Normalized box filter: Replace the original pixel value with the average value of the pixels around the pixel point, which will filter out the edge information of the image while filtering the noise.

[00⁸⁴] 2) Gaussian filter: Gaussian filter is the most commonly used filter with separable properties. It can convert two-dimensional Gaussian operation to one-dimensional Gaussian operation, which is essentially a low-pass filter.

[0085] 3) Median filter: The median filter replaces the original pixel with the median value in the neighborhood pixel set around the test pixel. When the median filter removes salt and pepper noise and patch noise, the effect is very obvious.

[00⁸⁶] 4) Bilateral filter: Bilateral filter can well retain the edge characteristics when smoothing the image, but its operation speed is relatively slow.

[0087] After the specific contours are formed in the above steps, contour orientation detection and contour delineation processing are required immediately, and edge detection is performed through some edge detection operators to achieve contour highlighting.

[0088] Edge detection processing technologies include but are not limited to the following technologies:

[0089] 1) Differential edge detection

[0090] 2) Reborts operator

[0091] 3) Sobel operator

[0092] 4) Prewitt operator

[0093] 5) Kirsch operator

[0094] 6) Laplace operator

[0095] 7) LOG operator

[0096] 8) Canny operator

[0097] Through the above-mentioned edge detection operators, the contour orientation detection and contour delineation processing are performed. The gradient operator is simple to calculate, but the accuracy is not high. It can only detect the approximate contour of the image, while the thinner edges may be ignored. . Prewitt and Sobel operators are better than Roberts. The detection effect of LOG filter and Canny operator is better than that of gradient operator, and can detect the thinner edge part of the image. Different systems, according to different environmental conditions and requirements, select appropriate operators to perform edge detection on images.

[0098] Through the above steps, the area covered by the signal and the area not covered by the signal can be distinguished in the signal coverage map corresponding to the area to be tested, so as to obtain the signal blind area, and it can be intuitively determined which areas are not covered by the base station. It can make the staff repair it in time.

[0099] On the basis of the foregoing embodiment, the performing base station performance evaluation according to the base station node parameters, system environment parameters, and network topology information to obtain the operating status information corresponding to each base station in the area to be tested includes:

[0100] According to the base station node parameters, system environment parameters and network topology information, the PageRank algorithm is used to calculate the PageRank score corresponding to each base station, and the operating status information of the corresponding base station is determined according to the PageRank score of each base station.

[0101] In a specific implementation process, FIG. 3 is a schematic diagram of a base station evaluation process provided by an embodiment of the present invention. As shown in FIG. 3, the specific evaluation steps include:

[01021 Step 301: Data conversion: When evaluating the performance of each base station, the status data collected by the analysis system is formatted in advance, and converted into the format required for the evaluation.

[0W³] Step 302: Calculate the load capacity of the base station; calculate the PageRank score corresponding to each base station through the PageRank algorithm, and further obtain the load capacity of the base station.

[0104] The PageRank algorithm is as follows:

[0105] 1) Determine each index value that affects the base station; where the index value is obtained by analyzing the base station node parameters, system environment parameters, and network topology information obtained by the system, and which specific index values can be obtained according to actual conditions;

[0106] 2) Determine the network topology of the emergency communication network; the network topology is obtained by the analysis system;

[0W⁷] 3) The link capability of the network topology is added to the basic PageRank algorithm. Specifically, the historical information of the base station is added to the PageRank algorithm. It can be understood that the historical information is the acquired historical base station node parameters.

[OW⁸] The basic principle of PageRank algorithm is as follows:

[01091 1) In the initial stage: the base station builds a Web graph through the link relationship, and each base station sets the same PageRank value. Through several rounds of calculation, the final PageRank value obtained by each base station will be obtained. With each round of calculation, the current PageRank value of the base station will be continuously updated.

[ΟΊΊΟ] 2) The calculation method of updating the PageRank score of the base station in one round: In the calculation of updating the PageRank score of the base station, each base station will evenly distribute its current PageRank value to the outgoing chain included in the base station, so that each base station A link gets the corresponding weight. And each base station sums up all the incoming weights of the incoming chain to the base station, and then a new PageRank score can be obtained. When each base station obtains the updated PageRank value, a round of PageRank calculation is completed.

[0Ί¹¹] The basic calculation formula of PageRank algorithm is as follows:

[0112]

Female) cut Σ :P_i:

Ton)

<img file="CN109472075A_D0001.tif" />

[0113] where PR is the PageRank score of the base station Pi, C (Pj) is the number of outgoing links of Pj, and Pj is the base station other than P and the base station among all the base stations included in the area to be tested; q is the damping coefficient ; N is the total number of base stations.

[0114] Assumption: If a set consists of only 4 base stations: A, B, C and D. If all base stations are linked to A, then the PR (PageRank) value of A will be the sum of B, C and D.

[0115] PR (Viii)=PR +PR +PR

[0116] Continue if B is also linked to C, and D is also linked to 3 base stations including A. A base station cannot vote twice. Therefore, B gives half a vote to each base station. Using the same logic, only one third of the votes cast by D is counted on A's PageRank.

[0117] PR(A)'PR(B) _t PRiC) 'PR(D) ~2~ -Ϊ- -3[0118]

[0119] In other words, the PR value of a base station is equally divided according to the total number of links.

CorpseΛ (.4)=:

PR(B) PR(, C) PRiC) -_: 4^- F -...:......:...,

L(B) L(C) L(C)

[0120] Because there are some base stations with a link number of 0, that is, those base stations that are not linked to any other base stations, which are also called isolated base stations, so that many base stations can be imitated. Therefore, it is necessary to modify the PageRank formula, that is, add a damping factor q to the simple formula, and q-generally, q = 0.85. Its meaning is the probability that the user arrives at a certain base station and continues to pass backwards at any time.

[0¹²¹] Step 303: Evaluate the load capacity of the base station; the load capacity of the base station can be estimated according to the PageRank score corresponding to each base station. The higher the PageRank score, the greater the current load of the base station and the lower its load capacity.

[0122] Step 304: Introduce an overloaded base station; set a preset threshold according to historical data, and compare the corresponding PageRank score of each base station with the preset threshold. If the PageRank score of a certain base station is greater than the preset threshold, it means that The base station is an overloaded base station.

[0123] Step 305: Early warning of overloaded base stations; warning of overloaded base stations.

[0124] The embodiment of the present invention uses base station node parameters, system environment parameters, and network topology information to perform simulation simulation and performance evaluation of base stations in the area to be tested to obtain corresponding signal coverage maps, signal blind areas, and operating status information of each base station. Thereby, the operating status of the communication system corresponding to the area to be measured can be obtained more accurately.

[0125] On the basis of the foregoing embodiment, the method further includes:

[0126] The signal coverage map, the signal blind zone, and the operating status information corresponding to each base station are displayed and stored, so that the staff can clearly and intuitively obtain the base station performance in the area to be tested.

[0127] Data storage technologies include but are not limited to the following technologies: 1) relational databases; 2) HDFS; 3) Hive; 4) HBase; 5) ElasticSearch; 6) PMML files; 7) other rules and knowledge storage formats.

[0128] On the basis of the foregoing embodiments, after acquiring the status data of all base stations in the communication system corresponding to the area to be tested, the method further includes:

[0129] A preprocessing operation is performed on the state data, wherein the preprocessing operation includes any one or a combination of missing processing, outlier processing, data integration, data discretization, and data standardization processing.

[0130] In the specific implementation process, after the analysis system obtains the status data, the status data needs to be previewed.

For processing operations, when collecting state data, it can be collected through the Extract-Transform-Load (ETL) subsystem. The main function of the ETL subsystem is to collect data from the database outside the system (including the relationship between various storage business data Extract the required data from the type database, document type, key-value type, graph type database, etc.) or files (such as the system or business log file of the user's access to information such as IP addresses), and perform necessary cleaning and conversion of the data, and then Stored in the big data storage system.

[0131] 1. ETL data collection methods include but are not limited to the following technologies:

[0132] 1) Combine data from multiple tables in the same database;

[0133] 2) Combine data from different tables and collections of multiple databases of the same type;

[0134] 3) Combine data from multiple databases of different types;

[0135] 4) Extract structured data from unstructured or semi-structured data;

[0136] 5) Extract a subset of the used fields or attributes from the original record or document.

[0137] Two. Data missing processing methods include but are not limited to the following technologies:

[0138] 1) Remove duplicate records;

[0139] 2) Delete records with missing fields or attributes of important significance;

[0140] 3) Remove fields or attributes with different field names or attribute names but the same meaning;

[0141] 4) Convert the type of the field or attribute, such as converting the date type to UTC integer;

[0142] 5) Convert continuous numeric types to discrete types, such as converting percentile scores to grades;

[0143] 6) Replace the missing attributes with the same constant (for example, "null" or mean value, etc.);

[0144] 7) Fill in with the most probable value (for example, use regression, Bayesian and other inference-based tools or decision tree induction to determine).

[0145] Three, abnormal value processing methods include but not limited to the following technologies:

[0146] 1) Directly delete outliers;

[0147] 2) For the time being, it will be retained for comprehensive analysis after the overall model is integrated;

[0148] 3) Replace with the mean value or other statistics;

[0149] 4) Treat it as a missing value and fill it with a statistical model.

[0150] Data integration mainly involves redundant processing and conflict data detection and processing. Data integration methods include but are not limited to the following technologies:

[0151] 1) Data redundancy: For numerical attributes, the correlation coefficient between attributes A and B is calculated to estimate the correlation between these two attributes. Remove one attribute from the two attributes, and use the remaining attributes to replace the two original attributes with greater correlation to reduce data redundancy

[0152] 2) Conflict data detection and processing: When matching the attributes of one database with another during data integration, the structure of the data should be considered to ensure that the attribute function dependencies and reference constraints in the original system match those in the target system .

[0153] (For example, weight attributes may be stored in metric units in one system and in English units in another system.)

[0154] Data standardization methods include but are not limited to the following technologies:

[0155] 1) min-max standardization;

[0156] 2) z-score standardization;

[0157] 3) Decimal scaling standardization;

[0 ΊMeasure 4) Vector normalization method;

[0159] 5) Linear proportional transformation method;

[0160] 6) Average method;

[0161] 7) Index conversion method.

[0162] Data discretization methods include but are not limited to the following technologies:

[0163] 1) Group distance grouping: Group distance grouping is the most basic method of data binning, including equidistant grouping and non-equal distance grouping. Equidistant grouping: The difference between the upper and lower limits of each group is equal. Non-equidistant grouping: the difference between the upper limit and the lower limit of each group is not equal. If the grouped data is used as an input variable in subsequent modeling to predict the classification of output variables, inappropriate group distance grouping may make some sample sizes unbalanced and affect the effect of the model.

[0164] 2) Quantile grouping: Dividing into number grouping and doing equal frequency grouping is to divide the observation points into n equal parts, and the number of observation points contained in each part is the same. (For example: There are 50,000 subscriptions for a certain main package, and the equal frequency segmentation needs to arrange the users in order according to the order time. After the arrangement, you can divide all users into ten segments evenly according to groups of 5,000.)

[0165] 3) Univariate grouping: Univariate grouping is also called rank grouping. The method is to sort all variables in descending or ascending order, and the sorting position is the grouping result, that is, the variables with the same value are grouped into the same group.

[0166] 4) Discretization based on information entropy.

[0167] In the embodiments of the present invention, by using base station node parameters, system environment parameters, and network topology information to perform simulation simulation and performance evaluation of the base stations in the area to be tested, the corresponding signal coverage map, signal blind zone, and operating status information of each base station are obtained. Thereby, the operating status of the communication system corresponding to the area to be measured can be obtained more accurately.

[0168] FIG. 4 is a schematic structural diagram of a base station performance analysis system provided by an embodiment of the present invention. As shown in FIG. 4, the system includes: a data acquisition module 401, an analog simulation module 402, and a performance evaluation module 403, wherein,

[0169] The data collection module 401 is used to obtain the status data of all base stations in the communication system corresponding to the area to be tested. The status data includes base station node parameters, system environment parameters, and network topology information; Base station node parameters, system environment parameters, and network topology information are used for dynamic simulation to obtain a signal coverage map corresponding to the area to be tested, and identify signal blind areas based on the signal coverage map; the performance evaluation module 403 is used to perform dynamic simulation based on the base station Node parameters, system environment parameters, and network topology information are evaluated for base station performance, and operating status information corresponding to each base station in the area to be tested is obtained.

[0170] Those skilled in the art can clearly understand that, for the convenience and conciseness of the description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method, which will not be repeated here.

[0171] In summary, the embodiment of the present invention uses base station node parameters, system environment parameters, and network topology information to perform simulation and performance evaluation of base stations in the area to be tested to obtain corresponding signal coverage maps, signal blind areas, and base stations. The operating status information of the system can more accurately know the operating status of the communication system corresponding to the area to be tested.

[0172] FIG. 5 is a schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. As shown in FIG. 5, the electronic device includes: a processor 501, a memory 502, and a bus 503; wherein,

[0173] The processor 501 and the memory 502 communicate with each other through the bus 503;

[0174] The processor 501 is configured to call program instructions in the memory 502 to execute the methods provided in the foregoing method embodiments, for example, including: obtaining status data of all base stations in the communication system corresponding to the area to be tested, The status data includes base station node parameters, system environment parameters, and network topology information; dynamic simulation is performed according to the base station node parameters, system environment parameters, and network topology information to obtain the signal coverage map corresponding to the area to be tested, and according to The signal coverage map identifies signal blind areas; and performs base station performance evaluation according to the base station node parameters, system environment parameters, and network topology information to obtain operating status information corresponding to each base station in the area to be tested.

[0175] This embodiment discloses a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer When the computer is able to execute the methods provided in the foregoing method embodiments, for example, including: obtaining state data of all base stations in the communication system corresponding to the area to be tested, the state data including base station node parameters, system environment parameters, and network topology information; Perform dynamic simulation based on the base station node parameters, system environment parameters, and network topology information to obtain a signal coverage map corresponding to the area to be tested, and identify signal blind areas based on the signal coverage map; and according to the base station node parameters , System environment parameters and network topology information perform base station performance evaluation, and obtain operating status information corresponding to each base station in the area to be tested.

[0176] This embodiment provides a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute the methods provided in the foregoing method embodiments , For example, including: acquiring status data of all base stations in the communication system corresponding to the area to be tested, the status data including base station node parameters, system environment parameters, and network topology information; according to the base station node parameters, system environment parameters, and network topology information Perform dynamic simulation to obtain a signal coverage map corresponding to the area to be tested, and identify signal blind areas based on the signal coverage map; and perform base station performance evaluation based on the base station node parameters, system environment parameters, and network topology information to obtain Operation status information corresponding to each base station in the area to be tested.

[0177] In the several embodiments provided in this application, it should be understood that the disclosed device and method may also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible implementation architecture, functions, and functions of the devices, methods, and computer program products according to multiple embodiments of the present invention. operating. In this regard, each block in the flowchart or block diagram may represent a module, program segment, or part of the code, and the module, program segment, or part of the code contains one or more functions for realizing the specified logic function. Executable instructions. It should also be noted that in some alternative implementations, the functions marked in the block may also occur in a different order from the order marked in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, or they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and/or flowchart, and the combination of the blocks in the block diagram and/or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions Or it can be realized by a combination of dedicated hardware and computer instructions.

[0178] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part. [0179] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present invention essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage media include: U disk, mobile hard disk, read-only memory ®0M, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program code .

[0180] The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0181] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or changes within the technical scope disclosed by the present invention. All replacements should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims. [0182] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply these entities. Or there is any such actual relationship or sequence between operations. Moreover, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes those that are not explicitly listed Other elements of, or also include elements inherent to this process, method, article or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other same elements in the process, method, article, or equipment that includes the element.