Wireless network evaluation method, device, electronic device and storage medium

Abstract

This application provides a wireless network assessment method, apparatus, electronic device, and storage medium. These methods obtain a comprehensive value for an activity scenario based on the user values ​​and number of participating users, as well as the level of the activity scenario. Based on communication data from the area where the activity scenario is located, they calculate the coverage and quality values ​​of the activity scenario, and combine this with the capacity value to determine the wireless network level of the activity scenario. This solution conveniently and efficiently implements wireless network assessment through a comprehensive analysis of multiple parameters, including user level, activity level, number of participants, event time, network coverage, network quality, and network capacity.

Description

Technical Field

[0001] The present application relates to communication technology, and in particular to a wireless network evaluation method, device, electronic device, and storage medium. Background Art

[0002] The purpose of wireless network assessment is to analyze network operation data to provide a reasonable assessment of network planning quality, current network operation status, existing problems and hidden dangers, and network investment utilization. This allows for a comprehensive understanding of the overall wireless network operation status and provides a reference for network optimization, network construction, and network assurance. Network assessment is necessary to accurately determine the level of network assurance required for different levels of user activity, providing appropriate assurance levels.

[0003] However, existing wireless network assessments mostly require manual on-site testing, which is rather cumbersome. Summary of the Invention

[0004] The present application provides a wireless network evaluation method, device, electronic device and storage medium for conveniently performing wireless network evaluation.

[0005] In a first aspect, the present application provides a wireless network evaluation method, comprising:

[0006] Determine the first user value corresponding to the participating user based on the user information under each user value; determine the first level value corresponding to the activity scene based on the activity information under each level value; and evaluate the first user volume of the participating user;

[0007] Calculating a comprehensive value of the activity scene based on the first user value, the first level value, and the first user quantity; calculating a coverage value of the activity scene based on reference signal received power data of the area where the activity scene is located; calculating a quality value of the activity scene based on signal-to-noise ratio data of the area where the activity scene is located; and obtaining a capacity value of the activity scene based on capacity indicator data of historical activity scenes;

[0008] According to the comprehensive value, coverage value, quality value and capacity value of the activity scene, the evaluation value of the activity scene is calculated, and the wireless network level of the activity scene is determined based on the evaluation value, wherein different levels of wireless network levels correspond to different evaluation value intervals.

[0009] Optionally, calculating the comprehensive value of the activity scenario according to the first user value, the first level value, and the first user quantity includes:

[0010] Based on the first formula, the comprehensive value P of the activity scene is calculated:

[0011] Among them, V i is the i-th first user value, n is the number of first user values, f(α) is the first level value, and N is the first user quantity.

[0012] Optionally, calculating an evaluation value of the activity scenario according to the comprehensive value, coverage value, quality value, and capacity value of the activity scenario, and determining the wireless network level of the activity scenario based on the evaluation value includes:

[0013] Based on the second formula, the evaluation value M of the activity scene is calculated:

[0014] M=P×ω1+C×ω2+Q×ω3+L×ω4

[0015] Where P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω1 is the weight coefficient of the comprehensive value; ω2 is the weight coefficient of the coverage value; ω3 is the weight coefficient of the quality value; ω4 is the weight coefficient of the capacity value; where ω1+ω2+ω3+ω4=1;

[0016] According to the evaluation value of the activity scenario, based on evaluation value intervals corresponding to different wireless network levels, the wireless network level of the activity scenario is determined.

[0017] Optionally, calculating the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located includes:

[0018] Obtaining, based on the reference signal received power data of the area where the activity scene is located, a first proportion of position points in the area whose reference signal received power data is not less than a predetermined power threshold among the position points;

[0019] Based on the third formula, the coverage value C of the activity scene is calculated: C=100×(1-r); wherein r is the first ratio.

[0020] Optionally, calculating the quality value of the activity scene according to signal-to-noise ratio data of the area where the activity scene is located includes:

[0021] Obtaining, based on the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points in the area whose signal-to-noise ratio data is not less than a predetermined gain threshold;

[0022] Based on the fourth formula, the quality value Q of the activity scene is calculated: Q=100×(1−q); wherein q is the second ratio.

[0023] Optionally, obtaining the capacity value of the activity scene according to the capacity indicator data of the historical activity scene includes:

[0024] Obtaining a maximum number of users in a historical activity scenario of the same type, where the maximum number of users is calculated based on an indicator parameter of the cell where the historical activity scenario of the same type is located during the activity period; wherein the indicator parameter includes at least one of the following: a busy hour downlink channel PRB resource utilization rate and an RRC connection;

[0025] Calculate the average number of users of the maximum number of users of the same type of historical activity scene, and calculate the number of cells C1 of the activity scene based on the fifth formula: Wherein, β is the preset user occupancy rate, N is the first number of users, is the average number of users;

[0026] Based on the sixth formula, the capacity value L of the activity scenario is calculated as follows: L=100×(C1-C2) / C1; wherein C2 is the number of online cells in the activity scenario.

[0027] Optionally, the method further includes:

[0028] Determining an occurrence frequency type of the activity scenario, where the occurrence frequency type includes a sudden type and a long-term type;

[0029] If the occurrence frequency type of the activity scene is a burst type, adjusting the wireless network level of the activity scene to a higher wireless network level;

[0030] If the occurrence frequency type of the activity scenario is a long-term type, the wireless network level adjustment is not performed.

[0031] In a second aspect, the present application provides a wireless network evaluation device, comprising:

[0032] a determination module, configured to determine a first user value corresponding to a participating user based on user information under each user value; determine a first level value corresponding to an activity scenario based on activity information under each level value; and evaluate a first user quantity of the participating user;

[0033] a calculation module, configured to calculate a comprehensive value of the activity scene based on the first user value, the first level value, and the first user quantity; calculate a coverage value of the activity scene based on reference signal received power data of the area where the activity scene is located; calculate a quality value of the activity scene based on signal-to-noise ratio data of the area where the activity scene is located; and obtain a capacity value of the activity scene based on capacity indicator data of historical activity scenes;

[0034] An evaluation module is used to calculate the evaluation value of the activity scene according to the comprehensive value, coverage value, quality value and capacity value of the activity scene, and determine the wireless network level of the activity scene based on the evaluation value, wherein different levels of wireless network levels correspond to different evaluation value intervals.

[0035] Optionally, the calculation module is specifically configured to calculate the comprehensive value P of the activity scene based on a first formula:

[0036] Among them, V i is the i-th first user value, n is the number of first user values, f(α) is the first level value, and N is the first user quantity.

[0037] Optionally, the evaluation module is specifically configured to calculate an evaluation value M of the activity scene based on a second formula:

[0038] M=P×ω1+C×ω2+Q×ω3+L×ω4

[0039] Where P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω1 is the weight coefficient of the comprehensive value; ω2 is the weight coefficient of the coverage value; ω3 is the weight coefficient of the quality value; ω4 is the weight coefficient of the capacity value; where ω1+ω2+ω3+ω4=1;

[0040] The evaluation module is further configured to determine the wireless network level of the activity scene according to the evaluation value of the activity scene and based on evaluation value intervals corresponding to different wireless network levels.

[0041] Optionally, the calculation module is specifically configured to obtain, based on the reference signal received power data of the area where the activity scene is located, a first proportion of position points whose reference signal received power data is not less than a predetermined power threshold among the position points in the area;

[0042] The calculation module is further configured to calculate the coverage value C of the activity scene based on a third formula: C=100×(1-r); wherein r is the first ratio.

[0043] Optionally, the calculation module is specifically configured to obtain, based on the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points in the area whose signal-to-noise ratio data is not lower than a predetermined gain threshold;

[0044] The calculation module is further configured to calculate the quality value Q of the activity scene based on a fourth formula: Q=100×(1-q); wherein q is the second ratio.

[0045] Optionally, the calculation module is specifically configured to obtain the capacity value of the activity scene based on the capacity indicator data of the historical activity scene, specifically including:

[0046] The calculation module is further configured to obtain a maximum number of users in a historical activity scenario of the same type, where the maximum number of users is calculated based on an indicator parameter of the cell where the historical activity scenario of the same type is located during the activity period; wherein the indicator parameter includes at least one of the following: a busy hour downlink channel PRB resource utilization rate and an RRC connection;

[0047] The calculation module is further configured to calculate the average number of users of the maximum number of users of the same type of historical activity scene, and calculate the number of cells C1 of the activity scene based on the fifth formula: Wherein, β is the preset user occupancy rate, N is the first number of users, is the average number of users;

[0048] The calculation module is further configured to calculate the capacity value L of the activity scenario based on the sixth formula: L=100=(C1-C2) / C1; wherein C2 is the number of online cells in the activity scenario.

[0049] Optionally, the device further includes:

[0050] An occurrence frequency identification module, configured to determine an occurrence frequency type of the activity scenario, wherein the occurrence frequency type includes a sudden type and a long-term type;

[0051] The occurrence frequency identification module is further configured to adjust the wireless network level of the activity scene to a higher level wireless network level if the occurrence frequency type of the activity scene is a burst type; and not perform wireless network level adjustment if the occurrence frequency type of the activity scene is a long-term type.

[0052] In a third aspect, the present application provides an electronic device, comprising:

[0053] at least one processor; and

[0054] a memory communicatively connected to the at least one processor; wherein,

[0055] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method according to the first aspect.

[0056] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in the first aspect.

[0057] This application provides a wireless network assessment method, apparatus, electronic device, and storage medium. These methods obtain a comprehensive value for an activity scenario based on the user values ​​and number of participating users, as well as the level of the activity scenario. Based on communication data from the area where the activity scenario is located, they calculate the coverage and quality values ​​of the activity scenario, and combine this with the capacity value to determine the wireless network level of the activity scenario. This solution conveniently and efficiently implements wireless network assessment through a comprehensive analysis of multiple parameters, including user level, activity level, number of participants, event time, network coverage, network quality, and network capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0059] Figure 1 Schematic diagram of the application scenario provided for this application example;

[0060] Figure 2 A flowchart of a wireless network evaluation method provided in Example 1 of the present application;

[0061] Figure 3 A flowchart of a wireless network evaluation method provided in Example 2 of the present application;

[0062] Figure 4 A flowchart of a wireless network evaluation method provided in Example 3 of the present application;

[0063] Figure 5 A schematic diagram of the structure of a wireless network evaluation device provided in Example 4 of the present application;

[0064] Figure 6 This is a structural diagram of an electronic device provided in Example 5 of the present application.

[0065] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0066] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0067] Figure 1 The application scenario diagram provided for this application example is as follows: Figure 1 As shown, wireless network assessment can be used to classify network security levels in various event scenarios. The box on the left side of the figure represents the existing technology. As can be seen from the figure, existing wireless network assessment methods mainly rely on manual on-site testing and analyze test data to determine the network coverage, quality, and other conditions of the event scenario, or directly determine the security level based on a single factor such as user level or activity level. Existing methods are time-consuming and costly in terms of manpower and material resources. When high-level users attend small or medium-sized events, the security level may be inaccurately positioned and the security strength may be deviated. However, the test data, user level, activity level, etc. in the above-mentioned existing technology can provide a basis for calculation and modeling in the wireless network assessment process.

[0068] Wireless network assessments can be performed by integrating user levels, activity levels, field test data, and historical data. As shown in the right box of the figure, a composite value reflecting user and activity levels can be derived based on the first user value, first level value, and first user volume. This composite value, along with coverage, quality, and capacity values ​​reflecting field test data, can be used to determine the wireless network assessment. This assessment, combined with the assessment value and occurrence frequency, allows for a complete wireless network assessment.

[0069] The technical solutions of the present application and the technical solutions of the present application are described in detail below with reference to specific embodiments. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in certain embodiments. In the description of the present application, unless otherwise clearly specified and limited, each term should be understood in a broad sense within the art. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0070] Example 1

[0071] Figure 2 A flowchart of a wireless network evaluation method provided in Example 1 of the present application is shown as follows: Figure 2 As shown, the method includes:

[0072] S101. Determine a first user value corresponding to a participating user based on user information under each user value; determine a first level value corresponding to an activity scenario based on activity information under each level value; and evaluate a first user quantity of the participating user;

[0073] S102: Calculate a comprehensive value of the activity scenario based on the first user value, the first level value, and the first user quantity;

[0074] S103. Calculate the coverage value of the activity scene based on the reference signal received power data of the area where the activity scene is located; calculate the quality value of the activity scene based on the signal-to-noise ratio data of the area where the activity scene is located; and obtain the capacity value of the activity scene based on the capacity indicator data of historical activity scenes.

[0075] S104. Calculate an evaluation value of the activity scene according to the comprehensive value, coverage value, quality value, and capacity value of the activity scene, and determine a wireless network level of the activity scene based on the evaluation value, wherein different levels of wireless network levels correspond to different evaluation value intervals.

[0076] This embodiment is illustrated with reference to specific application scenarios: wireless network assessment can be used to categorize network security levels in various activity scenarios, including gatherings, conferences, and large-scale public events. To implement wireless network assessment, parameters for network assessment must be determined and modeled. Typically, these parameters may include user levels, activity levels, field test data, and historical data.

[0077] A feasible implementation method is to use the first user value, the first level value and the first user quantity to derive a comprehensive value reflecting the user level and activity level. Through the comprehensive value and the coverage value, quality value and capacity value that can reflect the field test data, the evaluation value of the wireless network can be obtained, taking into account the evaluation value and occurrence frequency.

[0078] Combined with the scenario example: First, the first user value corresponding to the participating user can be determined based on the user information under each user value; the first level value corresponding to the activity scenario can be determined based on the activity information under each level value; and the first user quantity of the participating user can be evaluated.

[0079] The first user value can be used to reflect the user level. The user value can be divided into different intervals according to certain standards, and different intervals reflect the user's level. For example, the intervals can be divided into four intervals: I, II, III, and IV. Interval I indicates that the user is a provincial leader or a provincial company manager or above; interval II indicates that the user is a municipal leader or a municipal company manager or above, and below the provincial leader or provincial company manager; interval III indicates that the user is a district or county leader or a district or county company manager or above, and below the municipal leader or city company manager; interval IV indicates that the user is a district or county leader or a district or county company manager or below. The four intervals are set to correspond to different user values ​​V. i In practical applications, the sum of user values ​​can be set to 10, and the higher the user level, the higher the corresponding user value.

[0080] The first level value can be used to reflect the level of the event organizer. Generally speaking, the higher the level of the organizer, the stronger the security measures required. Specifically, the activity level refers to the level of the event organizer. If there are multiple organizers for a gathering, the highest-level organizer shall prevail. Activity levels can be divided into international, national, provincial, municipal, district, and county levels from high to low. Specifically, let f(α) be the activity level value. When the activity level is not lower than the national level, the activity level value can be 3; when the activity level is lower than the municipal level, the activity level value can be 1; when the activity level is not lower than the municipal level but lower than the national level, the activity level can be 2.

[0081] The first user volume is used to assess the size of an event. This refers to the number of attendees at a gathering. Taking into account the maximum number of users the event can accommodate and the user participation rate, it can be calculated as N = Kx. Here, N represents the number of people at the event, K represents the user participation rate, and 0 < K ≤ 1. x represents the maximum number of users the event can accommodate.

[0082] In one example, S102 may specifically include:

[0083] Based on the first formula, the comprehensive value P of the activity scene is calculated.

[0084] The first formula includes:

[0085] Among them, V i is the i-th first user value, n is the number of first user values, f(α) is the first level value, and N is the first user quantity.

[0086] This embodiment provides a feasible method for calculating a comprehensive value. In the first formula, the first level value is assigned based on the highest-level organizer. The first user value is calculated based on the user group present in the activity scenario. For example, if there are no users in interval I in the current activity scenario, there is no need to sum the user values ​​corresponding to interval I. The first user quantity is reflected in the form of an order of magnitude. The order of magnitude of the first user quantity can be obtained by taking the logarithm of the user quantity to the base 10.

[0087] The composite value is derived from the first user value, first level value, and first user volume. It comprehensively reflects the level of participating users, the level of activity, and the scale of an activity—the fundamental attributes of an activity. Furthermore, by considering only the highest-level organizer, the number of participating users, and the magnitude of the total user volume, calculations are greatly simplified, efficiency is improved, and the overall activity is more accurately reflected.

[0088] After obtaining the comprehensive value, a series of auxiliary indicators are still needed to conduct a comprehensive assessment of the level. One feasible implementation method is to use field test data for evaluation. If field test data cannot be obtained, simulation estimation can be performed based on historical data of similar scenarios. Specifically, the coverage value of the active scene is calculated based on the reference signal receiving power data of the area where the active scene is located; the quality value of the active scene is calculated based on the signal-to-noise ratio data of the area where the active scene is located; and the capacity value of the active scene is obtained based on the capacity indicator data of historical active scenes. The coverage value and quality value can reflect the signal quality under the active scene, and the capacity value can be used to simulate and estimate the current scene based on the data of historical similar scenes.

[0089] Finally, the evaluation value of the activity scenario can be calculated based on the comprehensive value, coverage value, quality value, and capacity value of the activity scenario, and the wireless network level of the activity scenario can be determined based on the evaluation value. Different levels of wireless network levels correspond to different evaluation value intervals. The interval to which the evaluation value M belongs can be divided according to actual conditions. In practical applications, a feasible way to select the dividing points is to divide the initial level into four intervals with 17.8, 11.12, and 6.08 as the boundaries. When M is not less than 17.8, it is defined as initial level S; when M is less than 17.8 but not less than 11.12, it is defined as initial level A; when M is less than 11.12 but not less than 6.08, it is defined as initial level B; when M is less than 6.08, it is defined as initial level C.

[0090] This embodiment provides a wireless network assessment method that derives a comprehensive value for an activity scenario based on the user values ​​and number of participating users, as well as the activity scenario's level. The method also calculates the coverage and quality values ​​of the activity scenario based on communication data in the area where the activity scenario occurs. This method, combined with the activity scenario's capacity value, determines the activity scenario's wireless network level. This solution conveniently and efficiently implements wireless network assessment through a comprehensive analysis of multiple parameters, including user level, activity level, number of participants, event time, network coverage, network quality, and network capacity.

[0091] Example 2

[0092] Figure 3 A flowchart of a wireless network evaluation method provided in Example 2 of the present application is used to illustrate the process of calculating the evaluation value of the activity scene based on the comprehensive value, coverage value, quality value and capacity value of the activity scene, and determining the wireless network level of the activity scene based on the evaluation value, such as Figure 3 As shown, based on any embodiment, S104 may specifically include:

[0093] S201 : Based on a second formula, obtain an evaluation value M of the activity scene by calculation.

[0094] The second formula includes: M=P×ω1+C×ω2+Q×ω3+L×ω4

[0095] Where P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω1 is the weight coefficient of the comprehensive value; ω2 is the weight coefficient of the coverage value; ω3 is the weight coefficient of the quality value; ω4 is the weight coefficient of the capacity value; where ω1+ω2+ω3+ω4=1;

[0096] S202: Determine the wireless network level of the activity scenario according to the evaluation value of the activity scenario and based on evaluation value intervals corresponding to different wireless network levels.

[0097] This embodiment is illustrated with reference to specific application scenarios: The second formula is a weighted average, which assigns different weights to the comprehensive value, coverage value, quality value and capacity value to obtain an evaluation value. Each weight coefficient is usually not specifically limited, but can be set according to actual conditions. For example, the values ​​of ω1 to ω4 can be 0.4, 0.2, 0.2, and 0.2, that is, a relatively large weight is assigned to the comprehensive value. After the evaluation value is calculated, the corresponding initial level can be obtained according to the implementation method of the initial level division described in Example 1.

[0098] In one example, calculating the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located in S103 specifically includes:

[0099] Obtaining, based on the reference signal received power data of the area where the activity scene is located, a first proportion of position points in the area whose reference signal received power data is not less than a predetermined power threshold among the position points;

[0100] Based on the third formula, the coverage value C of the activity scene is calculated: C=100×(1-r); wherein r is the first ratio.

[0101] Specifically, Reference Signal Received Power (RSRP) refers to the average power received by all resource elements carrying the reference signal within a symbol and is an important indicator for measuring network coverage. The RSRP value for each location in an activity scenario can be extracted from the Measurement Result (MR) data platform, and a threshold value, such as -110dBm, needs to be set for this value. The proportion of RSRP ≥ -110dBm is calculated and set to r. The corresponding coverage value C for different proportions can be obtained using C = 100 × (1-r).

[0102] The coverage value C reflects the network coverage rate in the active scenario in the form of a ratio by using the statistics of the environmental measurement value of the reference signal received power, which simplifies the description of the network coverage situation.

[0103] In another example, calculating the quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located in S103 specifically includes:

[0104] Obtaining, based on the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points in the area whose signal-to-noise ratio data is not less than a predetermined gain threshold;

[0105] Based on the fourth formula, the quality value Q of the activity scene is calculated: Q=100×(1−q); wherein q is the second ratio.

[0106] The signal-to-interference plus noise ratio (SINR) is defined as the ratio of the received useful signal strength to the interference signal strength, reflecting the relative strength of the effective signal. The SINR can also be obtained using the MR data platform, where the SNR value for each point in the scene is obtained. A threshold, such as 0dB, is also required for this value. The proportion of SINR values ​​≥ 0dB is calculated and set as q. The corresponding quality value Q for different ratios can be obtained using Q = 100 × (1-q).

[0107] Similar to the previous embodiment, the quality value Q measures the signal quality in the form of a ratio, which simplifies the description of the signal quality situation.

[0108] In another example, the step of obtaining the capacity value of the activity scene according to the capacity indicator data of the historical activity scene in S103 specifically includes:

[0109] Obtaining a maximum number of users in a historical activity scenario of the same type, where the maximum number of users is calculated based on an indicator parameter of the cell where the historical activity scenario of the same type is located during the activity period; wherein the indicator parameter includes at least one of the following: a busy hour downlink channel PRB resource utilization rate and an RRC connection;

[0110] Calculate the average number of users of the maximum number of users of the same type of historical activity scene, and calculate the number of cells C1 of the activity scene based on the fifth formula: Wherein, β is the preset user occupancy rate, N is the first number of users, is the average number of users;

[0111] Based on the sixth formula, the capacity value L of the activity scenario is calculated as follows: L=100×(C1-C2) / C1; wherein C2 is the number of online cells in the activity scenario.

[0112] The capacity requirements for event scenarios can be assessed by calculating capacity indicators for historical similar event scenarios. Specifically, first, a similar event scenario is selected, which can include concerts, sports events, press conferences, exhibitions, etc., based on the actual event scenario to be applied. Second, the capacity indicators of the cell occupied by similar gathering event scenarios during the most recent historical activity period are extracted. These capacity indicators include downlink channel PRB resource utilization during the cell's busy hour, the maximum number of users for RRC connection establishment, and downlink cell traffic. Finally, the capacity value L for the gathering event is calculated based on the capacity indicators.

[0113] For example, taking the busy hour downlink channel PRB resource utilization and RRC connection as an example, the specific example may be:

[0114] (1) In the unified network element management system, the busy hour downlink channel PRB resource utilization and the maximum number of users establishing RRC connections of the cells occupied by similar activity scenarios in the most recent historical activity time period are extracted. The busy hour statistics are all set to the maximum value of the daily busy hour.

[0115] (2) Based on the extracted index value, the cells with downlink channel PRB resource utilization between [80%, 85%] during busy hours are selected, and the maximum number of users establishing RRC connections corresponding to each record is obtained, which is recorded as RRC1, RRC2...RRC n Therefore, the average value of the maximum number of users establishing an RRC connection is for:

[0116]

[0117] Where n is the number of data records, Round to the nearest integer.

[0118] (3) The average value of the maximum number of users established based on the first user quantity N and the RRC connection Estimate the number of cells C1 that can meet the capacity requirements of the event site. The calculation method is as follows:

[0119]

[0120] Wherein, β is the user market share of a certain operator, β is rounded to two decimal places, and C1 is rounded to an integer.

[0121] (4) Count the number of cells in the network C2 in this activity scenario in the unified network element management system and calculate the capacity value L of the activity: L = 100 × (C1-C2) / C1

[0122] Wherein, L is rounded to an integer.

[0123] This embodiment constructs the relationship between historical activity scenarios of the same type and the activity scenarios to be evaluated, and uses at least one indicator of the busy hour downlink channel PRB resource utilization and RRC connection to analyze and model the various indicators of historical activity scenarios of the same type, thereby obtaining a simple method for expressing the capacity requirements of activity scenarios.

[0124] It should be noted that the above three implementation methods for calculating the coverage value, quality value and capacity value respectively can be implemented separately or in combination.

[0125] In this embodiment, a weighted average formula is used to calculate the activity scenario's evaluation value using the comprehensive value, coverage value, quality value, and capacity value. Based on the activity scenario's evaluation value and the evaluation value intervals corresponding to different wireless network levels, the wireless network level of the activity scenario is determined. This embodiment facilitates the calculation of the aforementioned indicators and quantifies the activity scenario's wireless network evaluation level using evaluation values ​​and their intervals.

[0126] Example 3

[0127] Figure 4 A flowchart of a wireless network evaluation method provided in Example 3 of this application is shown as follows: Figure 4 As shown, based on any embodiment, the method further includes:

[0128] S301: Determine the occurrence frequency type of the activity scenario, where the occurrence frequency type includes a sudden type and a long-term type;

[0129] S311: If the occurrence frequency type of the activity scene is a burst type, adjust the wireless network level of the activity scene to a higher wireless network level;

[0130] S310: If the occurrence frequency type of the activity scenario is a long-term type, wireless network level adjustment is not performed.

[0131] This embodiment is illustrated with reference to specific application scenarios: the occurrence frequency types of the activity scenarios may include burst type and long-term type. For burst type, the wireless network level assessment should be improved to strengthen the network security of the activity scenario; for long-term type, the initial level is directly used as the assessment level, and the corresponding level assessment and supporting services are performed based on the calculated evaluation value. Specifically, if the occurrence frequency is determined to be a long-term type, the scenario is directly divided into S, A, B, and C levels according to the calculated evaluation value. Correspondingly, if the occurrence frequency of the initial levels S, A, B, and C is a burst type, it is divided into S+, S, A, and B levels.

[0132] For example, take the Q Expo as an example to use this method to evaluate wireless networks. First, determine the user value V based on the participating users. i ={4, 3, 2, 1}, the activity level value f(α)=2 is determined according to the level of the sponsor, and N=600,000 is determined according to the number of people at the event site. The comprehensive value P=17.78 can be obtained through calculation.

[0133] Secondly, the SINR data of Hall A of the Convention and Exhibition Center was extracted on the MR data platform. The proportion r of RSRP ≥ -110dBm was 100%, and the coverage value C = 0 was obtained by calculation. The SINR data of Hall A was extracted on the MR data platform. The proportion q of SINR ≥ 0dB was 97.08%, and the quality value q = 2.92 was obtained by calculation.

[0134] Next, the unified network element management system extracts the downlink channel PRB resource utilization rate and the maximum number of users to establish RRC connections during the busy hour of all cells in the convention and exhibition center during a fixed time period. By screening cells with downlink channel PRB resource utilization rates between [80% and 85%] during the busy hour, the corresponding maximum number of users to establish RRC connections is averaged to obtain the average value of the maximum number of users to establish RRC connections. The number of cells that meet the capacity requirements of the event site is calculated to be C1 = 98, and the number of cells in the network is counted in the unified network element management system as C2 = 73, thereby calculating the capacity value L = 26.

[0135] Finally, the M value for this event is calculated as: M = P × 0.4 + C × 0.2 + Q × 0.2 + L × 0.2 = 12.896. This gives an initial rating of A. Since this expo is an annual event, its frequency should be long-term. Therefore, the final wireless network assessment result is an A-level network rating for this event scenario, and accordingly, an A-level network assurance level should be implemented.

[0136] In this embodiment, the occurrence frequency type of the activity scenario is first determined, which can be either sudden or long-term. If the occurrence frequency type of the activity scenario is sudden, the wireless network level of the activity scenario is adjusted to a higher level. If the occurrence frequency type of the activity scenario is long-term, the wireless network level adjustment is not performed. Whether the network assessment level should be increased is determined based on whether the activity scenario is sudden, thereby improving the reliability of the wireless network assessment.

[0137] Example 4

[0138] The fourth embodiment of the present application also provides an image recognition device to implement the above method. Figure 5 As shown, Figure 5 This is a structural diagram of a wireless network evaluation device provided in Embodiment 4 of the present application, the device comprising:

[0139] The determination module 41 is configured to determine a first user value corresponding to a participating user based on user information under each user value; determine a first level value corresponding to an activity scenario based on activity information under each level value; and evaluate a first user quantity of the participating user;

[0140] a calculation module 42 configured to calculate a comprehensive value of the activity scene based on the first user value, the first level value, and the first user quantity; calculate a coverage value of the activity scene based on reference signal received power data of the area where the activity scene is located; calculate a quality value of the activity scene based on signal-to-noise ratio data of the area where the activity scene is located; and obtain a capacity value of the activity scene based on capacity indicator data of historical activity scenes;

[0141] The evaluation module 43 is used to calculate the evaluation value of the activity scene according to the comprehensive value, coverage value, quality value and capacity value of the activity scene, and determine the wireless network level of the activity scene based on the evaluation value, wherein different levels of wireless network levels correspond to different evaluation value intervals.

[0142] This embodiment is exemplified in conjunction with specific application scenarios: the determination module 41 obtains the user value, user quantity and level value of the participating users of the activity scene; the calculation module 42 calculates the comprehensive value of the activity scene based on the data obtained by the determination module 41, and calculates the coverage value and quality value of the activity scene based on the communication data of the area where the activity scene is located, and obtains the capacity value of the activity scene based on the historical data of similar scenes; the evaluation module 43 performs weighted averaging on the data calculated by the calculation module 42 to calculate the evaluation value of the activity scene, and determines the wireless network level of the activity scene based on the evaluation value and the pre-divided evaluation value interval.

[0143] In one example, the calculation module 42 is specifically configured to calculate the comprehensive value P of the activity scene based on a first formula.

[0144] The first formula includes:

[0145] Among them, V i is the i-th first user value, n is the number of first user values, f(α) is the first level value, and N is the first user quantity.

[0146] In this embodiment, the calculation module specifically calculates a comprehensive value based on the first user value, the first level value, and the first user volume. This value comprehensively reflects the level of participating users, the level of activity, and the scale of the activity—that is, the basic attributes of an activity. Furthermore, by only considering the highest-level organizer, the number of participating users, and the magnitude of the total number of users, the calculation is greatly simplified, improving efficiency and more accurately reflecting the basic characteristics of the activity.

[0147] In one example, the evaluation module 43 is specifically configured to:

[0148] Based on the second formula, the evaluation value M of the activity scene is calculated.

[0149] The second formula includes: M=P×ω1+C×ω2+Q×ω3+L×ω4

[0150] Where P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω1 is the weight coefficient of the comprehensive value; ω2 is the weight coefficient of the coverage value; ω3 is the weight coefficient of the quality value; ω4 is the weight coefficient of the capacity value; where ω1+ω2+ω3ω4=1;

[0151] The evaluation module 43 is further configured to determine the wireless network level of the activity scenario according to the evaluation value of the activity scenario and based on the evaluation value intervals corresponding to different wireless network levels.

[0152] In this implementation, the evaluation module calculates an evaluation value for the activity scenario by taking a weighted average of the comprehensive value, coverage value, quality value, and capacity value. Based on the evaluation value and the evaluation value intervals corresponding to different wireless network levels, the evaluation module determines the wireless network level for the activity scenario. This implementation simplifies the calculation of the evaluation value and quantifies the wireless network evaluation level of the activity scenario in the form of the evaluation value and its interval.

[0153] In one example, the calculation module 42 may be specifically configured to:

[0154] Obtaining, based on the reference signal received power data of the area where the activity scene is located, a first proportion of position points in the area whose reference signal received power data is not less than a predetermined power threshold among the position points;

[0155] Based on the third formula, the coverage value C of the activity scene is calculated: C=100×(1-r); wherein r is the first ratio.

[0156] In this embodiment, RSRP is used to measure network coverage. RSRP values ​​for each location in an activity scenario can be extracted on the MR data platform. Calculation module 42 calculates the proportion of RSRP points above a predetermined threshold, sets this proportion to r, and calculates coverage values ​​C corresponding to different proportions using the formula C = 100 × (1-r). Coverage value C represents network coverage in an activity scenario as a ratio, using statistics from an environmental measurement of reference signal received power, simplifying the description of network coverage.

[0157] In another example, the calculation module 42 may be further configured to:

[0158] Obtaining, based on the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points in the area whose signal-to-noise ratio data is not less than a predetermined gain threshold;

[0159] Based on the fourth formula, the quality value Q of the activity scene is calculated: Q=100×(1−q); wherein q is the second ratio.

[0160] In this embodiment, the signal-to-noise ratio can reflect the relative size of the effective signal. Alternatively, the signal-to-noise ratio value for each location in the activity scene can be obtained using the MR data platform. Calculation module 42 can count the proportion of locations where the SINR is not less than a predetermined threshold, set this proportion as q, and calculate the corresponding quality value Q for different proportions using Q = 100 × (1-q). The quality value Q measures signal quality as a ratio, simplifying the description of signal quality.

[0161] In another example, the calculation module 42 is specifically configured to obtain the capacity value of the activity scene based on the capacity indicator data of the historical activity scene, specifically including:

[0162] The calculation module 42 is further configured to obtain a maximum number of users in a historical activity scenario of the same type, where the maximum number of users is calculated based on an indicator parameter of the cell where the historical activity scenario is located during the activity period; wherein the indicator parameter includes at least one of the following: a busy hour downlink channel PRB resource utilization rate and an RRC connection rate;

[0163] The calculation module 42 is further configured to calculate the average number of users of the maximum number of users of the same type of historical activity scene, and calculate the number of cells C1 of the activity scene based on the fifth formula: Wherein, β is the preset user occupancy rate, N is the first number of users, is the average number of users;

[0164] The calculation module 42 is further configured to calculate the capacity value L of the activity scenario based on the sixth formula: L=100×(C1-C2) / C1; wherein C2 is the number of online cells in the activity scenario.

[0165] In this embodiment, the calculation module 42 constructs the relationship between historical activity scenarios of the same type and the activity scenarios to be evaluated, and uses at least one indicator of the busy hour downlink channel PRB resource utilization and RRC connection to analyze and model the various indicators of historical activity scenarios of the same type, thereby obtaining a simple method for expressing the capacity requirements of activity scenarios.

[0166] In one example, the device further includes an occurrence frequency identification module, specifically configured to:

[0167] Determining an occurrence frequency type of the activity scenario, where the occurrence frequency type includes a sudden type and a long-term type;

[0168] The occurrence frequency identification module is further used to adjust the wireless network level of the activity scene to a higher level wireless network level if the occurrence frequency type of the activity scene is a sudden type; if the occurrence frequency type of the activity scene is a long-term type, no wireless network level adjustment is performed.

[0169] In this embodiment, the frequency identification module first determines the frequency type of the activity scenario, which can be either sudden or long-term. If the frequency type is sudden, the module adjusts the wireless network level of the activity scenario to a higher level. If the frequency type is long-term, no wireless network level adjustment is performed. The frequency identification module determines the final network assessment level based on whether the activity scenario is sudden, thereby improving the reliability of the wireless network assessment.

[0170] This embodiment provides a wireless network evaluation device. A determination module obtains the user value and user volume of participating users, as well as the level of an activity scenario. A calculation module calculates the comprehensive value of the activity scenario based on the indicators obtained by the determination module. It also calculates the coverage and quality values ​​of the activity scenario based on communication data in the area where the activity scenario is located, and obtains the capacity value of the activity scenario based on historical data of similar scenarios. The evaluation module takes a weighted average of the various indicators obtained by the calculation module to determine the wireless network level of the activity scenario. This device can be used to comprehensively analyze multiple parameters, such as user level, activity level, number of people, event time, network coverage, network quality, and network capacity, to conveniently and efficiently implement wireless network evaluation.

[0171] Example 5

[0172] Figure 6 This is a structural diagram of an electronic device provided in Example 5 of the present application, such as Figure 6 As shown, the electronic device includes:

[0173] The electronic device includes a processor 291 and a memory 292; a communication interface 293, and a bus 294. The processor 291, memory 292, and communication interface 293 can communicate with each other via bus 294. Communication interface 293 can be used for information transmission. The processor 291 can invoke logic instructions in memory 294 to execute the methods of the above embodiments.

[0174] In addition, the logic instructions in the memory 292 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0175] Memory 292, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of the present application. Processor 291 executes the software programs, instructions, and modules stored in memory 292 to perform functional applications and data processing, thereby implementing the methods in the above-mentioned method embodiments.

[0176] Memory 292 may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal device. Memory 292 may also include high-speed random access memory and non-volatile memory.

[0177] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in any embodiment.

[0178] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0179] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A wireless network evaluation method, characterized in that: include: Determine the first user value corresponding to the participating user based on the user information under each user value; Determine a first level value corresponding to the activity scenario based on activity information at each level value; and evaluate a first user quantity of the participating users; Calculating a comprehensive value of the activity scene based on the first user value, the first level value, and the first user quantity; calculating a coverage value of the activity scene based on reference signal received power data of an area where the activity scene is located; and calculating a quality value of the activity scene based on signal-to-noise ratio data of the area where the activity scene is located; Obtaining a capacity value of the activity scene based on capacity indicator data of historical activity scenes; Calculating an evaluation value of the activity scenario according to the comprehensive value, coverage value, quality value, and capacity value of the activity scenario, and determining a wireless network level of the activity scenario based on the evaluation value, wherein different levels of wireless network levels correspond to different evaluation value intervals; The acquiring the capacity value of the activity scene according to the capacity indicator data of the historical activity scene includes: Obtaining a maximum number of users in a historical activity scenario of the same type, where the maximum number of users is calculated based on an indicator parameter of the cell where the historical activity scenario of the same type is located during the activity period; wherein the indicator parameter includes at least one of the following: a busy hour downlink channel physical resource block (PRB) resource utilization rate and a radio resource control (RRC) connection rate; Calculate the average number of users of the maximum number of users of the same type of historical activity scene, and calculate the number of cells C1 of the activity scene based on the fifth formula: Wherein, β is the preset user occupancy rate, N is the first number of users, is the average number of users; Based on the sixth formula, the capacity value L of the activity scenario is calculated as follows: L=100×(C1-C2) / C1; wherein C2 is the number of online cells in the activity scenario.

2. The method according to claim 1, characterized in that Calculating the comprehensive value of the activity scenario according to the first user value, the first level value, and the first user quantity includes: Based on the first formula, the comprehensive value P of the activity scene is calculated: Among them, V i is the i-th first user value, n is the number of first user values, and f(α) is the first level value.

3. The method according to claim 2, characterized in that The calculating an evaluation value of the activity scenario according to the comprehensive value, coverage value, quality value, and capacity value of the activity scenario, and determining the wireless network level of the activity scenario based on the evaluation value, includes: Based on the second formula, the evaluation value M of the activity scene is calculated: M=P×ω1+C×ω2+Q×ω3+L×ω4 Where P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω1 is the weight coefficient of the comprehensive value; ω2 is the weight coefficient of the coverage value; ω3 is the weight coefficient of the quality value; ω4 is the weight coefficient of the capacity value; where ω1+ω2+ω3+ω4=1; According to the evaluation value of the activity scenario, based on evaluation value intervals corresponding to different wireless network levels, the wireless network level of the activity scenario is determined.

4. The method according to claim 1, wherein The calculating the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located includes: Obtaining, based on the reference signal received power data of the area where the activity scene is located, a first proportion of position points in the area whose reference signal received power data is not less than a predetermined power threshold among the position points; Based on the third formula, the coverage value C of the activity scene is calculated: C=100×(1-r); wherein r is the first ratio.

5. The method according to claim 1, characterized in that Calculating the quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located includes: Obtaining, based on the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points in the area whose signal-to-noise ratio data is not less than a predetermined gain threshold; Based on the fourth formula, the quality value Q of the activity scene is calculated: Q=100×(1−q); wherein q is the second ratio.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: Determining an occurrence frequency type of the activity scenario, where the occurrence frequency type includes a sudden type and a long-term type; If the occurrence frequency type of the activity scene is a burst type, adjusting the wireless network level of the activity scene to a higher wireless network level; If the occurrence frequency type of the activity scenario is a long-term type, the wireless network level adjustment is not performed.

7. A wireless network evaluation device, characterized in that: include: A determination module, configured to determine a first user value corresponding to a participating user based on user information under each user value; Determine the first level value corresponding to the activity scene based on the activity information under each level value; evaluating a first user quantity of the participating user; a calculation module, configured to calculate a comprehensive value of the activity scene based on the first user value, the first level value, and the first user quantity; calculate a coverage value of the activity scene based on reference signal received power data of an area where the activity scene is located; and calculate a quality value of the activity scene based on signal-to-noise ratio data of the area where the activity scene is located; Obtaining a capacity value of the activity scene based on capacity indicator data of historical activity scenes; an evaluation module, configured to calculate an evaluation value of the activity scenario based on the comprehensive value, coverage value, quality value, and capacity value of the activity scenario, and determine a wireless network level of the activity scenario based on the evaluation value, wherein different levels of wireless network levels correspond to different evaluation value intervals; The calculation module is further configured to: obtain a maximum number of users in a historical activity scenario of the same type, where the maximum number of users is calculated based on an indicator parameter of a cell in which the historical activity scenario of the same type is located during an activity period; wherein the indicator parameter includes at least one of the following: a busy-hour downlink channel physical resource block (PRB) resource utilization rate and a radio resource control (RRC) connection rate; calculate an average number of users of the maximum number of users in the historical activity scenario of the same type, and calculate the number of cells C1 of the activity scenario based on the fifth formula: Wherein, β is the preset user occupancy rate, N is the first number of users, is the average number of users; based on the sixth formula, the capacity value L of the activity scenario is calculated: L = 100 × (C1-C2) / C1; wherein C2 is the number of online cells in the activity scenario.

8. The device according to claim 7, characterized in that The calculation module is specifically configured to calculate the comprehensive value P of the activity scene based on the first formula: Among them, V i is the i-th first user value, n is the number of first user values, and f(α) is the first level value.

9. The device according to claim 7, characterized in that The evaluation module is specifically configured to calculate an evaluation value M of the activity scene based on a second formula: M=P×ω1+C×ω2+Q×ω3+L×ω4 Where P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω1 is the weight coefficient of the comprehensive value; ω2 is the weight coefficient of the coverage value; ω3 is the weight coefficient of the quality value; ω4 is the weight coefficient of the capacity value; where ω1+ω2+ω3+ω4=1; The evaluation module is further configured to determine the wireless network level of the activity scene according to the evaluation value of the activity scene and based on evaluation value intervals corresponding to different wireless network levels.

10. The device according to claim 7, characterized in that The calculation module is specifically configured to obtain, based on the reference signal received power data of the area where the activity scene is located, a first proportion of the position points in the area whose reference signal received power data is not less than a predetermined power threshold among the position points; The calculation module is further configured to calculate the coverage value C of the activity scene based on a third formula: C=100×(1-r); wherein r is the first ratio.

11. The device according to claim 7, characterized in that The calculation module is specifically configured to obtain, based on the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points in the area whose signal-to-noise ratio data is not less than a predetermined gain threshold. The calculation module is further configured to calculate the quality value Q of the activity scene based on a fourth formula: Q=100×(1-q); wherein q is the second ratio.

12. The device according to any one of claims 7 to 11, characterized in that The device further comprises: An occurrence frequency identification module, configured to determine an occurrence frequency type of the activity scenario, wherein the occurrence frequency type includes a sudden type and a long-term type; The occurrence frequency identification module is further configured to adjust the wireless network level of the activity scene to a higher level wireless network level if the occurrence frequency type of the activity scene is a burst type; and not perform wireless network level adjustment if the occurrence frequency type of the activity scene is a long-term type.

13. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

14. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

Images