CN115996412A - Wireless network evaluation method, device, electronic equipment and storage medium - Google Patents

Abstract

The application provides a wireless network evaluation method, a wireless network evaluation device, electronic equipment and a storage medium, wherein the comprehensive value of an activity scene is obtained according to the user value, the user quantity and the level value of the activity scene of a participating user, the coverage value and the quality value of the activity scene are calculated based on communication data of an area where the activity scene is located, and the wireless network level of the activity scene is determined by combining the capacity value of the activity scene. According to the scheme, wireless network evaluation is conveniently and conveniently realized through comprehensive analysis of multiple parameters such as user level, activity level, people number scale, event time, network coverage, network quality, network capacity and the like.

Description

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

Technical Field

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

Background Art

The purpose of wireless network assessment is to analyze network operation data and provide a reasonable assessment of network planning quality, current network operation status, problems and hidden dangers in network operation, network investment utilization rate, etc., so as to fully understand the overall operation status of the wireless network and provide reference for network optimization, network construction and network security. In different levels and different user activity scenarios, network assessment is needed to accurately locate the level of network security in order to provide security strength that matches the activity scenario.

However, existing wireless network assessments mostly require manual on-site testing, which is rather cumbersome.

Summary of the invention

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

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

Determine the first user value corresponding to the participating user according to the user information under each user value; determine the first level value corresponding to the activity scene according to the activity information under each level value; and evaluate the first user quantity of the participating user;

Calculate the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; calculate the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located; calculate the quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; obtain the capacity value of the activity scene according to the capacity indicator data of the historical activity scene;

According to the comprehensive value, coverage value, quality value and capacity value of the activity scene, an 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.

Optionally, calculating the comprehensive value of the activity scene 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, _Vi 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.

Optionally, calculating the evaluation value of the activity scene according to 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 includes:

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

M＝P×ω ₁ +C×ω ₂ +Q×ω ₃ +L×ω ₄

Wherein, P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω ₁ is the weight coefficient of the comprehensive value; ω ₂ is the weight coefficient of the coverage value; ω ₃ is the weight coefficient of the quality value; ω ₄ is the weight coefficient of the capacity value; where, ω ₁ +ω ₂ +ω ₃ +ω ₄ =1;

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

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:

According to the reference signal received power data of the area where the activity scene is located, obtaining 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;

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.

Optionally, 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:

According to the signal-to-noise ratio data of the area where the activity scene is located, obtaining a second proportion of the position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold among the position points in the area;

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.

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

其中，β为预设的用户占有率，N为所述第一用户量，

为所述平均用户数；The average number of users of the maximum number of users of the same type of historical activity scene is calculated, and the number of cells C ₁ of the activity scene is calculated based on the fifth formula:

Wherein, β is the preset user occupancy rate, N is the first user quantity,

is the average number of users;

Based on the sixth formula, the capacity value L of the activity scenario is calculated: L=100×(C ₁ −C ₂ )/C ₁ ; wherein C ₂ is the number of online cells of the activity scenario.

Optionally, the method further includes:

Determine 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 scene is a long-term type, the wireless network level adjustment is not performed.

In a second aspect, the present application provides a wireless network evaluation device, including:

A determination module, configured to determine a first user value corresponding to a participating user according to user information under each user value; determine a first level value corresponding to an activity scene according to activity information under each level value; and evaluate a first user quantity of the participating user;

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

An evaluation module is used to 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 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.

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

Among them, _Vi 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.

Optionally, the evaluation module is specifically configured to calculate and obtain the evaluation value M of the activity scene based on a second formula:

M＝P×ω ₁ +C×ω ₂ +Q×ω ₃ +L×ω ₄

Wherein, P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω ₁ is the weight coefficient of the comprehensive value; ω ₂ is the weight coefficient of the coverage value; ω ₃ is the weight coefficient of the quality value; ω ₄ is the weight coefficient of the capacity value; where, ω ₁ +ω ₂ +ω ₃ +ω ₄ =1;

The evaluation module is further specifically 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.

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

The calculation module is specifically used 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.

Optionally, the calculation module is specifically used to obtain, according to the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold among the position points in the area;

The calculation module is specifically further used 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.

Optionally, the calculation module is specifically used to obtain the capacity value of the activity scene according to the capacity indicator data of the historical activity scene, and specifically includes:

The calculation module is further specifically used to obtain the maximum number of users in the same type of historical activity scene, and the maximum number of users is calculated based on the indicator parameters of the cell where the same type of historical activity scene is located in the activity period; wherein the indicator parameters include at least one of the following: busy downlink channel PRB resource utilization and RRC connection;

其中，β为预设的用户占有率，N为所述第一用户量，

为所述平均用户数；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 scenes, and obtain the number of cells C ₁ of the activity scene based on the fifth formula:

Wherein, β is the preset user occupancy rate, N is the first user quantity,

is the average number of users;

The calculation module is further configured to calculate the capacity value L of the activity scene based on the sixth formula: L=100=(C ₁ -C ₂ )/C ₁ ; wherein C ₂ is the number of online cells of the activity scene.

Optionally, the device further comprises:

An occurrence frequency identification module, used to determine the occurrence frequency type of the activity scene, the occurrence frequency type including a sudden type and a long-term type;

The occurrence frequency identification module is also 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 burst type; if the occurrence frequency type of the activity scene is a long-term type, no wireless network level adjustment is performed.

In a third aspect, the present application provides an electronic device, including:

at least one processor; and

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 the first aspect.

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.

The present application provides a wireless network evaluation method, device, electronic device and storage medium, which obtains the comprehensive value of the activity scene according to the user value of the participating users, the user volume and the level value of the activity scene, 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 determines the wireless network level of the activity scene in combination with the capacity value of the activity scene. The solution conveniently and easily implements wireless network evaluation through comprehensive analysis of multiple parameters such as user level, activity level, number of people, event time, network coverage, network quality, and network capacity.

BRIEF DESCRIPTION OF THE DRAWINGS

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.

FIG1 is a schematic diagram of an application scenario provided by an example of this application;

FIG2 is a schematic diagram of a wireless network evaluation method provided in Example 1 of the present application;

FIG3 is a flow chart of a wireless network evaluation method provided in Embodiment 2 of the present application;

FIG4 is a schematic diagram of a wireless network evaluation method provided in Embodiment 3 of the present application;

FIG5 is a schematic diagram of the structure of a wireless network evaluation device provided in Embodiment 4 of the present application;

FIG6 is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of the present application.

The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments.

DETAILED DESCRIPTION

Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

FIG1 is a schematic diagram of the application scenario provided by the example of this application. As shown in FIG1 , wireless network evaluation can be used to divide network security levels in various activity scenarios. The box on the left side of the figure represents the prior art. As can be seen from the figure, the existing wireless network evaluation method mainly conducts on-site testing manually, and judges the network coverage, quality, etc. of the activity scene by analyzing the test data, or directly determines the security level based on a single factor such as user level or activity level as a reference. The existing method is time-consuming and has high manpower and material costs. When high-level users attend small and medium-sized events, there may be problems such as inaccurate positioning of the security level and deviations in the security strength. However, the test data, user level, activity level, etc. in the above-mentioned prior art can provide a basis for calculation and modeling in the process of wireless network evaluation.

Wireless network evaluation can be performed by comprehensively applying user level, activity level, field test data, historical data, etc. As shown in the right box of the figure, a comprehensive value reflecting the user level and activity level can be obtained based on the first user value, the first level value and the first user quantity. The evaluation value of the wireless network can be obtained through the comprehensive value and the coverage value, quality value and capacity value that can reflect the field test data. The wireless network evaluation can be completed by comprehensively considering the evaluation value and the occurrence frequency.

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

Embodiment 1

FIG. 2 is a flow chart of a wireless network evaluation method provided in Embodiment 1 of the present application. As shown in FIG. 2 , the method includes:

S101, determining a first user value corresponding to a participating user according to user information under each user value; determining a first level value corresponding to an activity scene according to activity information under each level value; and evaluating a first user quantity of the participating user;

S102, calculating a comprehensive value of the activity scene according to the first user value, the first level value, and the first user quantity;

S103, 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; 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; and obtaining the capacity value of the activity scene according to the capacity indicator data of the historical activity scene;

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 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.

This embodiment is exemplified in conjunction with a specific application scenario: wireless network assessment can be used to classify the level of network assurance in various activity scenarios, and the activity scenarios may include gathering scenarios, conference scenarios, large-scale public activities, etc. In order to implement wireless network assessment, it is necessary to determine parameters for network assessment and perform modeling, and generally, the parameters may include user level, activity level, field test data, and historical data.

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, an evaluation value of the wireless network can be derived, which comprehensively considers the evaluation value and the frequency of occurrence.

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.

The first user value can be used to reflect the user level, and the user value can be divided into different intervals according to certain standards, and different intervals reflect the user level. For example, the interval can be divided into four intervals: I, II, III, and IV, where 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 municipal company manager; interval IV indicates that the user is a district or county leader or a district or county company manager or below, and four intervals are set to correspond to different user values V _i , respectively. In actual applications, the sum of the user values can be set to 10, and the higher the user level, the higher the corresponding user value.

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 is required. Specifically, the activity level refers to the level of the event organizer. If there are multiple organizers for a party, the highest level organizer shall prevail. Activity levels can be divided into international, national, provincial, municipal, district, county, etc. 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.

The first user volume is used to evaluate the scale of the number of people at an event, which refers to the number of participants at the gathering event site. Taking into account the maximum number of users that the event site can accommodate and the user participation rate, it can be calculated by N=Kx. Among them, N represents the number of people at the event site, K represents the user participation rate, 0＜K≤1, and x represents the maximum number of users that the event site can accommodate.

In one example, S102 may specifically include:

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

Wherein, the first formula includes:

Among them, _Vi 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.

This implementation provides a feasible way to calculate the comprehensive value. In the first formula, the first level value is assigned according to the highest-level organizer; in the first user value, the user group existing in the activity scene is used to calculate the user value. For example, if there are no users in interval I in the current activity scene, 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. Taking the logarithm of the user quantity with a base of 10, the order of magnitude of the first user quantity can be obtained.

The comprehensive value is derived from the first user value, the first level value and the first user volume, and can comprehensively reflect the level of participating users, the level of activities and the scale of activities, that is, the basic attributes of an activity. In addition, only considering the highest-level organizer, the value of users participating in the activity and the order of magnitude of the total number of users can greatly simplify the calculation, improve the efficiency of use, and more accurately reflect the basic situation of the activity.

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 in 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.

Finally, the evaluation value of the activity scene can be calculated according to the comprehensive value, coverage value, quality value and capacity value of the activity scene, and the wireless network level of the activity scene can be determined based on the evaluation value, wherein 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 the actual situation. In practical applications, a feasible way to select the division 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 the initial level S, when M is less than 17.8 but not less than 11.12, it is defined as the initial level A, when M is less than 11.12 but not less than 6.08, it is defined as the initial level B, and when M is less than 6.08, it is defined as the initial level C.

This embodiment provides a wireless network evaluation method, which obtains the comprehensive value of the activity scene according to the user value of the participating users, the user volume and the level value of the activity scene, 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 determines the wireless network level of the activity scene in combination with the capacity value of the activity scene. This solution conveniently and easily implements wireless network evaluation through comprehensive analysis of multiple parameters such as user level, activity level, number of people, event time, network coverage, network quality, and network capacity.

Embodiment 2

FIG3 is a flow chart of a wireless network evaluation method provided in Embodiment 2 of the present application, which is used to illustrate the process of calculating the evaluation value of the activity scene according to 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. As shown in FIG3, based on any embodiment, S104 may specifically include:

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

Wherein, the second formula includes: M = P×ω ₁ + C×ω ₂ + Q×ω ₃ + L×ω ₄

Wherein, P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω ₁ is the weight coefficient of the comprehensive value; ω ₂ is the weight coefficient of the coverage value; ω ₃ is the weight coefficient of the quality value; ω ₄ is the weight coefficient of the capacity value; where, ω ₁ +ω ₂ +ω ₃ +ω ₄ =1;

S202: 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.

This embodiment is illustrated in combination with 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 ω ₁ to ω ₄ can be 0.4, 0.2, 0.2, and 0.2, that is, a relatively large weight is assigned to the comprehensive value. After calculating the evaluation value, the corresponding initial level can be obtained according to the implementation method of the initial level division described in Example 1.

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:

According to the reference signal received power data of the area where the activity scene is located, obtaining 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;

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.

Specifically, the Reference Signal Receiving Power (RSRP) refers to the average value of the power received on all resource elements that carry the reference signal in a symbol, and is an important indicator for measuring network coverage. The RSRP value of each location point in the activity scenario can be extracted on the Measurement Result (MR) data platform, and a threshold value, such as -110dBm, needs to be set for the value. The proportion of RSRP ≥ -110dBm is counted, and the proportion is set to r. The corresponding coverage value C under different proportions can be obtained through C = 100 × (1-r).

The coverage value C reflects the network coverage rate in the activity scenario in the form of a ratio by using the statistics of the environmental measurement value of the reference signal receiving power, thereby simplifying the description of the network coverage situation.

In another example, the step of 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:

According to the signal-to-noise ratio data of the area where the activity scene is located, obtaining a second proportion of the position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold among the position points in the area;

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.

The signal-to-interference plus noise ratio (SINR) data is defined as the ratio of the received useful signal strength to the interference signal strength, which can reflect the relative size of the effective signal. The signal-to-noise ratio can also be obtained through the MR data platform, where the signal-to-noise ratio value of each location point in the activity scene is obtained. It is also necessary to set a threshold for this value, such as 0dB. The proportion of SINR ≥ 0dB is counted, and the proportion is set to q. The corresponding quality value Q under different proportions can be obtained through Q = 100 × (1-q).

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

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:

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

其中，β为预设的用户占有率，N为所述第一用户量，

为所述平均用户数；The average number of users of the maximum number of users of the same type of historical activity scene is calculated, and the number of cells C1 of the activity scene is calculated based on the fifth formula:

Wherein, β is the preset user occupancy rate, N is the first user quantity,

is the average number of users;

Based on the sixth formula, the capacity value L of the activity scenario is calculated: L=100×(C ₁ −C ₂ )/C ₁ ; wherein C ₂ is the number of online cells of the activity scenario.

The assessment of the capacity demand of the activity scene can be calculated through the capacity indicators of the historical activity scenes of the same type. Specifically, first, a similar activity scene is selected, which may include concerts, sports events, press conferences, exhibitions, etc., and is selected according to the actual activity scene to be applied. Secondly, the capacity indicators of the cell occupied by similar party activity scenes in the most recent historical activity time period are extracted. The capacity indicators include the downlink channel PRB resource utilization rate during the busy time of the cell, the maximum number of users for establishing RRC connections, downlink cell traffic, etc. Finally, the capacity value L of the party activity is calculated based on the capacity indicators.

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

(1) In the unified network element management system, the busy-hour downlink channel PRB resource utilization rate 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, and the busy-hour statistics are set to the maximum value of the busy hour of the day.

为：(2) Based on the extracted index values, the cells with downlink channel PRB resource utilization rates between [80%, 85%] during busy hours are selected, and the maximum number of users for establishing RRC connections corresponding to each record is obtained, which is recorded as RRC ₁ , RRC ₂ , ...RRC _n . Therefore, the average value of the maximum number of users for establishing RRC connections is

for:

根据四舍五入法保留至整数位。Where n is the number of data records,

Round to the nearest integer.

估算满足活动现场容量需求的小区数C₁，计算方法如下：(3) According to the first user quantity N and the average value of the maximum number of users established by RRC connection

Estimate the number of cells C ₁ that meet the capacity requirements of the event site, and calculate it as follows:

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.

(4) The number of cells in the network in this activity scenario C ₂ is counted in the unified network element management system, and the capacity value L of the activity is calculated: L = 100 × (C ₁ -C ₂ )/C ₁

Wherein, L is rounded to an integer.

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 indicators of historical activity scenarios of the same type, thereby obtaining a simple method for expressing the capacity requirements of activity scenarios.

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.

In this embodiment, a weighted average formula is used to calculate the evaluation value of the activity scene by comprehensive value, coverage value, quality value, and capacity value, and the wireless network level of the activity scene is determined based on the evaluation value intervals corresponding to different wireless network levels according to the evaluation value of the activity scene. Through this embodiment, the aforementioned indicators can be conveniently calculated, and the wireless network evaluation level of the activity scene can be quantified in the form of evaluation values and their intervals.

Embodiment 3

FIG4 is a flow chart of a wireless network evaluation method provided in Embodiment 3 of the present application. As shown in FIG4 , based on any embodiment, the method further includes:

S301, determining an occurrence frequency type of the activity scene, where the occurrence frequency type includes a sudden type and a long-term type;

S311, 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 level of wireless network level;

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

This embodiment is exemplified in combination with specific application scenarios: the occurrence frequency type of the activity scene may include a burst type and a long-term type. For the burst type, the wireless network level assessment should be improved to increase the strength of the activity scene network security; for the long-term type, the initial level is directly used as the assessment level, and the corresponding level assessment and supporting services are performed according to the calculation result of the evaluation value. Specifically, if the occurrence frequency is determined to be a long-term type, the scene 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 of S, A, B, and C is a burst type, it is divided into S+, S, A, and B levels.

In one example, the wireless network evaluation is performed using the Q Expo. First, the user value V _i = {4, 3, 2, 1} is determined based on the participating users, the activity level value f(α) = 2 is determined based on the level of the sponsor, and N = 600,000 is determined based on the number of people at the event site. The comprehensive value P = 17.78 can be obtained through calculation.

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

通过计算得到满足活动现场容量需求的小区数C₁＝98，在统一网元管理系统统计在网小区数量C₂＝73，从而计算出容量值L＝26。Thirdly, the unified network element management system extracts the downlink channel PRB resource utilization rate and the maximum number of users for RRC connection establishment during the busy hours of all cells in the exhibition center in a fixed time period. By screening the cells with the downlink channel PRB resource utilization rate between [80%, 85%] during the busy hours, the corresponding maximum number of users for RRC connection establishment is averaged to obtain the average value of the maximum number of users for RRC connection establishment.

The number of cells that meet the capacity requirements of the activity site is calculated to be C ₁ =98, and the number of cells in the network is counted in the unified network element management system as C ₂ =73, thereby calculating the capacity value L=26.

Finally, the M value of this event is calculated as: M = P × 0.4 + C × 0.2 + Q × 0.2 + L × 0.2 = 12.896, and the initial level is A. Since the expo is an annual event, the frequency type should be long-term, so the final result of the wireless network assessment is that the network level of the event scene is A, and accordingly, the network guarantee with A level of strength should be implemented.

In this embodiment, the occurrence frequency type of the activity scene is first determined, and the occurrence frequency type includes a burst type and a long-term type; if the occurrence frequency type of the activity scene is a burst type, the wireless network level of the activity scene is adjusted to a higher level wireless network level; if the occurrence frequency type of the activity scene is a long-term type, the wireless network level adjustment is not performed. According to whether the activity scene is an emergency event, it is determined whether the network evaluation level should be improved, thereby improving the reliability of the wireless network evaluation.

Embodiment 4

Embodiment 4 of the present application also provides an image recognition device to implement the above method. As shown in FIG5 , FIG5 is a schematic diagram of the structure of a wireless network evaluation device provided in Embodiment 4 of the present application, the device comprising:

The determination module 41 is used to determine the first user value corresponding to the participating user according to the user information under each user value; determine the first level value corresponding to the activity scene according to the activity information under each level value; and evaluate the first user quantity of the participating user;

The calculation module 42 is used to calculate the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; calculate the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located; calculate the quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; and obtain the capacity value of the activity scene according to the capacity indicator data of the historical activity scene;

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.

The present implementation is exemplified in conjunction with specific application scenarios: the determination module 41 obtains the user value of the participating users, the number of users and the level value 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, calculates 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.

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.

Wherein, the first formula includes:

Among them, _Vi 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.

In this embodiment, the calculation module can specifically obtain a comprehensive value based on the first user value, the first level value and the first user quantity, which can comprehensively reflect the level of participating users, the level of activities and the scale of activities, that is, the basic attributes of an activity. In addition, only the highest-level organizer, the value of users participating in the activity and the order of magnitude of the total number of users are considered, which can greatly simplify the calculation, improve the use efficiency, and more accurately reflect the basic situation of the activity.

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

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

Wherein, the second formula includes: M = P×ω ₁ + C×ω ₂ + Q×ω ₃ + L×ω ₄

Wherein, P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω ₁ is the weight coefficient of the comprehensive value; ω ₂ is the weight coefficient of the coverage value; ω ₃ is the weight coefficient of the quality value; ω ₄ is the weight coefficient of the capacity value; where, ω ₁ +ω ₂ +ω ₃ ω ₄ =1;

The evaluation module 43 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 the evaluation value intervals corresponding to different wireless network levels.

In this implementation, the evaluation module performs a weighted average of the comprehensive value, coverage value, quality value, and capacity value to calculate the evaluation value of the activity scene, and determines the wireless network level of the activity scene based on the evaluation value intervals corresponding to different wireless network levels according to the evaluation value of the activity scene. This implementation simplifies the calculation of the evaluation value and quantifies the wireless network evaluation level of the activity scene in the form of the evaluation value and its interval.

In one example, the calculation module 42 may be specifically used for:

According to the reference signal received power data of the area where the activity scene is located, obtaining 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;

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.

In this embodiment, RSRP is used to measure network coverage, and the RSRP value of each location point in the activity scene can be extracted on the MR data platform. The calculation module 42 can count the proportion of RSRP not less than the predetermined threshold, set the proportion as r, and obtain the corresponding coverage value C under different proportions through C=100×(1-r). The coverage value C reflects the network coverage in the activity scene in the form of a proportion by counting the environmental measurement value of the reference signal received power, which simplifies the description of the network coverage situation.

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

According to the signal-to-noise ratio data of the area where the activity scene is located, obtaining a second proportion of the position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold among the position points in the area;

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.

In this embodiment, the signal-to-noise ratio can reflect the relative size of the effective signal, and the signal-to-noise ratio value of each position point in the activity scene can also be obtained through the MR data platform. The calculation module 42 can count the proportion of SINR not less than the predetermined threshold, set the proportion as q, and obtain the corresponding quality value Q under different proportions through Q=100×(1-q). The quality value Q measures the signal quality in the form of a ratio, which simplifies the description of the signal quality situation.

In another example, the calculation module 42 is specifically configured to obtain the capacity value of the activity scene according to the capacity indicator data of the historical activity scene, and specifically includes:

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

其中，β为预设的用户占有率，N为所述第一用户量，

为所述平均用户数；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 scenes, and obtain the number of cells C ₁ of the activity scene based on the fifth formula:

Wherein, β is the preset user occupancy rate, N is the first user quantity,

is the average number of users;

The calculation module 42 is further configured to calculate the capacity value L of the activity scene based on the sixth formula: L=100×(C ₁ −C ₂ )/C ₁ ; wherein C ₂ is the number of online cells of the activity scene.

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.

In one example, the device further includes an occurrence frequency identification module, which is specifically used to:

Determine an occurrence frequency type of the activity scenario, where the occurrence frequency type includes a sudden type and a long-term type;

The occurrence frequency identification module is also 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 burst type; if the occurrence frequency type of the activity scene is a long-term type, no wireless network level adjustment is performed.

In this embodiment, the occurrence frequency identification module first determines the occurrence frequency type of the activity scene, including the sudden type and the long-term type; if the occurrence frequency type of the activity scene is the sudden type, the occurrence frequency identification module adjusts 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 the long-term type, the wireless network level adjustment is not performed. The occurrence frequency identification module determines the adjustment of the final network evaluation level according to whether the activity scene is an emergency event, thereby improving the reliability of the wireless network evaluation.

This embodiment provides a wireless network evaluation device, wherein the determination module obtains the user value of participating users, the number of users, and the level value of the activity scene; the calculation module calculates the comprehensive value of the activity scene based on the indicators obtained by the determination module, 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 similar scene data; the evaluation module performs weighted average on the various indicators obtained by the calculation module to determine the wireless network level of the activity scene. The device can be used to comprehensively analyze multiple parameters such as user level, activity level, number of people, event time, network coverage, network quality, network capacity, etc., and conveniently and easily realize wireless network evaluation.

Embodiment 5

FIG6 is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of the present application. As shown in FIG6 , the electronic device includes:

The electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, the memory 292, and the communication interface 293 may communicate with each other through the bus 294. The communication interface 293 may be used for information transmission. The processor 291 may call the logic instructions in the memory 294 to execute the method of the above embodiment.

In addition, the logic instructions in the above-mentioned 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.

The memory 292 is a computer-readable storage medium that 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. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, that is, implementing the methods in the above method embodiments.

The memory 292 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 292 may include a high-speed random access memory and may also include a non-volatile memory.

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.

Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

It should be understood that the present application is not limited to the precise structures that have been 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 (16)

1. A wireless network evaluation method, comprising: Determine the first user value corresponding to the participating user according to the user information under each user value; determine the first level value corresponding to the activity scene according to the activity information under each level value; and evaluate the first user quantity of the participating user; Calculate the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; calculate the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located; calculate the quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; obtain the capacity value of the activity scene according to the capacity indicator data of the historical activity scene; According to the comprehensive value, coverage value, quality value and capacity value of the activity scene, an 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. 2. The method according to claim 1, characterized in that the calculating the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity comprises: Based on the first formula, the comprehensive value P of the activity scene is calculated:

Among them, _Vi 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. 3. The method according to claim 2, characterized in that the step of calculating the evaluation value of the activity scene according to 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 comprises: Based on the second formula, the evaluation value M of the activity scene is calculated: M＝P×ω ₁ +C×ω ₂ +Q×ω ₃ +L×ω ₄ Wherein, P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω ₁ is the weight coefficient of the comprehensive value; ω ₂ is the weight coefficient of the coverage value; ω ₃ is the weight coefficient of the quality value; ω ₄ is the weight coefficient of the capacity value; where, ω ₁ +ω ₂ +ω ₃ +ω ₄ =1; According to the evaluation value of the activity scene, based on the evaluation value intervals corresponding to different wireless network levels, the wireless network level of the activity scene is determined. 4. The method according to claim 1, characterized in that the calculation of the coverage value of the activity scene according to the reference signal received power data of the area where the activity scene is located comprises: According to the reference signal received power data of the area where the activity scene is located, obtaining 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; 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 the step of 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 comprises: According to the signal-to-noise ratio data of the area where the activity scene is located, obtaining a second proportion of the position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold among the position points in the area; 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 claim 1, characterized in that the obtaining of the capacity value of the activity scene according to the capacity indicator data of the historical activity scene comprises: Obtaining a maximum number of users in a historical activity scene of the same type, where the maximum number of users is calculated based on an indicator parameter in an activity period of a cell where the historical activity scene of the same type is located; wherein the indicator parameter includes at least one of the following: a physical resource block (PRB) resource utilization rate of a downlink channel during a busy period and a radio resource control (RRC) connection; The average number of users of the maximum number of users of the same type of historical activity scene is calculated, and the number of cells C ₁ of the activity scene is calculated based on the fifth formula:

Wherein, β is the preset user occupancy rate, N is the first user quantity,

is the average number of users; Based on the sixth formula, the capacity value L of the activity scenario is calculated: L=100×(C ₁ −C ₂ )/C ₁ ; wherein C ₂ is the number of online cells of the activity scenario. 7. The method according to any one of claims 1 to 6, characterized in that the method further comprises: Determine 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 scene is a long-term type, the wireless network level adjustment is not performed. 8. A wireless network evaluation device, comprising: A determination module, configured to determine a first user value corresponding to a participating user according to user information under each user value; determine a first level value corresponding to an activity scene according to activity information under each level value; and evaluate a first user quantity of the participating user; a calculation module, configured to calculate a comprehensive value of the activity scene according to the first user value, the first level value, and the first user quantity; calculate a coverage value of the activity scene according to reference signal received power data of the area where the activity scene is located; calculate a quality value of the activity scene according to signal-to-noise ratio data of the area where the activity scene is located; and obtain a capacity value of the activity scene according to capacity indicator data of historical activity scenes; An evaluation module is used to 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 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. 9. The device according to claim 8, characterized in that The calculation module is specifically used to calculate the comprehensive value P of the activity scene based on the first formula:

Among them, _Vi 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. 10. The device according to claim 8, characterized in that The evaluation module is specifically used to calculate and obtain the evaluation value M of the activity scene based on the second formula: M＝P×ω ₁ +C×ω ₂ +Q×ω ₃ +L×ω ₄ Wherein, P is the comprehensive value; C is the coverage value; Q is the quality value; L is the capacity value; ω ₁ is the weight coefficient of the comprehensive value; ω ₂ is the weight coefficient of the coverage value; ω ₃ is the weight coefficient of the quality value; ω ₄ is the weight coefficient of the capacity value; where, ω ₁ +ω ₂ +ω ₃ +ω ₄ =1; The evaluation module is further specifically 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. 11. The device according to claim 8, characterized in that The calculation module is specifically used to obtain, according to the reference signal received power data of the area where the activity scene is located, a first proportion of the position points whose reference signal received power data is not less than a predetermined power threshold among the position points in the area; The calculation module is specifically used 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. 12. The device according to claim 8, characterized in that The calculation module is specifically used to obtain, according to the signal-to-noise ratio data of the area where the activity scene is located, a second proportion of the position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold among the position points in the area; The calculation module is specifically further used 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. 13. The device according to claim 8, characterized in that The calculation module is specifically used to obtain the capacity value of the activity scene according to the capacity indicator data of the historical activity scene, and specifically includes: The calculation module is further specifically used to obtain the maximum number of users in the same type of historical activity scene, and the maximum number of users is calculated based on the indicator parameters of the cell where the same type of historical activity scene is located in the activity period; wherein the indicator parameters include at least one of the following: busy downlink channel PRB resource utilization and RRC connection; 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 scenes, and obtain the number of cells C ₁ of the activity scene based on the fifth formula:

Wherein, β is the preset user occupancy rate, N is the first user quantity,

is the average number of users; The calculation module is further configured to calculate the capacity value L of the activity scene based on the sixth formula: L=100×(C ₁ −C ₂ )/C ₁ ; wherein C ₂ is the number of online cells of the activity scene. 14. The device according to any one of claims 8 to 13, characterized in that the device further comprises: An occurrence frequency identification module, used to determine the occurrence frequency type of the activity scene, the occurrence frequency type including a sudden type and a long-term type; The occurrence frequency identification module is also 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 burst type; if the occurrence frequency type of the activity scene is a long-term type, no wireless network level adjustment is performed. 15. An electronic device comprising: at least one processor; and 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 7. 16. A computer-readable storage medium, characterized in that 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 according to any one of claims 1 to 7.

Images