CN115996412A - Wireless network evaluation method, device, electronic equipment and storage medium - Google Patents
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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
Technical Field
The present disclosure relates to communication technologies, and in particular, to a wireless network evaluation method, a wireless network evaluation device, an electronic device, and a storage medium.
Background
The wireless network evaluation aims at reasonably evaluating the network planning quality, the current network operation condition, problems and hidden dangers existing in the network operation, the network investment utilization rate and the like through analyzing the network operation data so as to fully master the overall wireless network operation condition and provide references for network optimization, network construction and network guarantee. In the activity scenes of different grades and different users, the grade of network guarantee is accurately positioned through network evaluation so as to provide the guarantee strength matched with the activity scenes.
However, in the existing wireless network evaluation, manual field test is required, and the evaluation is complicated.
Disclosure of Invention
The application provides a wireless network evaluation method, a wireless network evaluation device, electronic equipment and a storage medium, which are used for conveniently and rapidly evaluating a wireless network.
In a first aspect, the present application provides a wireless network evaluation method, including:
determining a first user value corresponding to the participating user according to the user information under each user value; determining a first level value corresponding to the activity scene according to the activity information under each level value; evaluating a first user quantity of the participating user;
calculating the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; according to the reference signal receiving power data of the area where the active scene is located, calculating the coverage value of the active scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; acquiring a capacity value of a historical activity scene according to capacity index data of the activity scene;
and calculating an evaluation value of the activity scene according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and determining the wireless network grade of the activity scene based on the evaluation value, wherein the wireless network grade of different grades corresponds to different evaluation value intervals.
Optionally, the calculating the integrated value of the activity scene according to the first user value, the first level value and the first user quantity includes:
based on a first formula, calculating a comprehensive value P of the activity scene:
wherein V is i For the i 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 calculating the evaluation value of the activity scene according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and determining the wireless network level of the activity scene based on the evaluation value includes:
based on a second formula, calculating and obtaining an evaluation value M of the activity scene:
M＝P×ω 1 +C×ω 2 +Q×ω 3 +L×ω 4
wherein P is a comprehensive value; c is a coverage value; q is a mass value; l is a capacity value; omega 1 The weight coefficient is the integrated value; omega 2 A weight coefficient that is a coverage value; omega 3 Weight coefficients for the mass values; omega 4 A weight coefficient for the capacity value; wherein omega 1 +ω 2 +ω 3 +ω 4 ＝1；
And determining the wireless network grade of the activity scene based on the evaluation value intervals corresponding to different wireless network grades according to the evaluation value of the activity scene.
Optionally, the calculating the coverage value of the active scene according to the reference signal received power data of the area where the active scene is located includes:
According to the reference signal received power data of the area where the active scene is located, obtaining a first proportion of the position points of which the reference signal received power data is not lower than a preset power threshold value in the position points of the area;
based on a third formula, calculating and obtaining a coverage value C of the activity scene: c=100× (1-r); wherein r is the first ratio.
Optionally, the calculating the quality value of the active scene according to the signal-to-noise ratio data of the area where the active scene is located includes:
obtaining second proportions of the position points of which the signal to noise ratio data is not lower than a preset gain threshold value in each position point of the region according to the signal to noise ratio data of the region where the active scene is located;
based on a fourth formula, calculating and obtaining a quality value Q of the activity scene: q=100× (1-Q); wherein q is the second ratio.
Optionally, the acquiring the capacity value of the activity scene according to the capacity index data of the historical activity scene includes:
acquiring the maximum number of users of the activity scenes with the same type of history, wherein the maximum number of users is obtained by calculating index parameters in an activity period based on a cell in which the activity scenes with the same type of history are located; wherein the index parameter includes at least one of: resource utilization rate of a busy downlink channel PRB and RRC connection;
Calculating the average number of the maximum number of users of the activity scenes with the same type of history, and calculating the cell number C of the activity scenes based on a fifth formula 1 ：
Wherein beta is a preset user occupancy, N is the first user quantity, < + >>
The average number of users;
based on a sixth formula, calculating and obtaining a capacity value L of the activity scene: l=100× (C 1 -C 2 )/C 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein C is 2 And the number of the network cells in the activity scene.
Optionally, the method further comprises:
determining the occurrence frequency type of the activity scene, wherein the occurrence frequency type comprises a burst type and a long-term type;
if the occurrence frequency type of the active scene is a burst type, adjusting the wireless network level of the active scene to be a wireless network level of a higher level;
if the occurrence frequency type of the activity scene is a long-term type, wireless network level adjustment is not performed.
In a second aspect, the present application provides a wireless network evaluation apparatus, including:
the determining module is used for determining a first user value corresponding to the participating user according to the user information under each user value; determining a first level value corresponding to the activity scene according to the activity information under each level value; evaluating a first user quantity of the participating user;
The calculation module is used for calculating the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; according to the reference signal receiving power data of the area where the active scene is located, calculating the coverage value of the active scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; acquiring a capacity value of a historical activity scene according to capacity index data of the activity scene;
and the evaluation module is used for calculating an evaluation value of the activity scene according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and determining the wireless network grade of the activity scene based on the evaluation value, wherein the wireless network grades of different grades correspond to different evaluation value intervals.
Optionally, the computing moduleThe method is specifically used for calculating the comprehensive value P of the activity scene based on a first formula:
wherein V is i For the i 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 an 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 a comprehensive value; c is a coverage value; q is a mass value; l is a capacity value; omega 1 The weight coefficient is the integrated value; omega 2 A weight coefficient that is a coverage value; omega 3 Weight coefficients for the mass values; omega 4 A weight coefficient for the capacity value; wherein omega 1 +ω 2 +ω 3 +ω 4 ＝1；
The evaluation module is specifically further configured to determine, according to the evaluation value of the activity scene, a wireless network level of the activity scene based on evaluation value intervals corresponding to different wireless network levels.
Optionally, the calculating module is specifically configured to obtain, according to reference signal received power data of an area where the active scene is located, a first proportion of a location point whose reference signal received power data is not lower than a predetermined power threshold value in the location points of the area;
the calculating module is specifically further configured to calculate and obtain a coverage value C of the activity scene based on a third formula: c=100× (1-r); wherein r is the first ratio.
Optionally, the calculating module is specifically configured to obtain, according to signal-to-noise ratio data of an area where the active scene is located, a second proportion of the location points of the area, where the signal-to-noise ratio data is not lower than a predetermined gain threshold, in the location points;
The calculating module is specifically further configured to calculate and obtain a quality value Q of the active scene based on a fourth formula: q=100× (1-Q); wherein q is the second ratio.
Optionally, the calculating module is specifically configured to obtain, according to capacity index data of a historical activity scene, a capacity value of the activity scene, and specifically includes:
the calculation module is specifically configured to obtain a maximum number of users of the same type of historical activity scenes, where the maximum number of users is obtained by calculating index parameters in an activity period based on a cell where the same type of historical activity scenes are located; wherein the index parameter includes at least one of: resource utilization rate of a busy downlink channel PRB and RRC connection;
the calculation module is specifically configured to calculate an average number of maximum users of the activity scenes of the same type, and calculate a cell number C of the activity scenes based on a fifth formula 1 ：
Wherein beta is a preset user occupancy, N is the first user quantity, < + >>
The average number of users;
the calculation module is specifically further configured to calculate and obtain a capacity value L of the activity scene based on a sixth formula: l=100= (C 1 -C 2 )/C 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein C is 2 And the number of the network cells in the activity scene.
Optionally, the apparatus further includes:
the occurrence frequency identification module is used for determining the occurrence frequency type of the activity scene, wherein the occurrence frequency type comprises a burst type and a long-term type;
the occurrence frequency identification module is further configured to adjust a wireless network level of the active scene to a wireless network level of a higher level if the occurrence frequency type of the active scene is a burst type; if the occurrence frequency type of the activity scene is a long-term type, wireless network level adjustment is not performed.
In a third aspect, the present application provides an electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium having stored therein computer-executable instructions for performing the method according to the first aspect when executed by a processor.
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.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic view of an application scenario provided in an example of the present application;
fig. 2 is a flowchart of a wireless network evaluation method according to a first embodiment of the present application;
fig. 3 is a flowchart of a wireless network evaluation method according to a second embodiment of the present application;
fig. 4 is a flow chart of a wireless network evaluation method according to a third embodiment of the present application;
Fig. 5 is a schematic structural diagram of a wireless network evaluation device according to a fourth embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present application.
Specific embodiments thereof have been shown by way of example in the drawings and will herein be described in more detail. These drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
Fig. 1 is a schematic view of an application scenario provided by an example of the present application, as shown in fig. 1, a wireless network evaluation may be used for network security classification in various activity scenarios. The left side of the diagram represents the prior art, and the diagram shows that the prior wireless network evaluation method mainly carries out field test manually and judges the conditions of network coverage, quality and the like of an activity scene by analyzing test data, or directly determines the security level by taking a single factor such as a user level or an activity level as a reference. The existing method is long in time consumption, high in cost of manpower and material resources, and when a high-level user attends a small-sized and medium-sized event, the problem that the guarantee level is positioned inaccurately and the guarantee force is deviated can occur. However, the test data, user level, activity level, etc. in the above prior art may provide basis for calculation and modeling in the wireless network evaluation process.
The wireless network evaluation can be performed by comprehensively applying user level, activity level, field test data, historical data and the like. As shown in the right box of the figure, according to the first user value, the first level value and the first user quantity, a comprehensive value for reflecting the user level and the activity level can be obtained, the evaluation value of the wireless network can be obtained through the comprehensive value and the coverage value, the quality value and the capacity value capable of reflecting the field test data, the evaluation value and the occurrence frequency are comprehensively considered, and the wireless network evaluation can be completed.
The technical scheme of the present application and the technical scheme of the present application are described in detail below with specific examples. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. In the description of the present application, the terms are to be construed broadly in the art, unless explicitly stated or defined otherwise. Embodiments of the present application will be described below with reference to the accompanying drawings.
Example 1
Fig. 2 is a schematic flow chart of a wireless network evaluation method according to an embodiment of the present application, as shown in fig. 2, where 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 the activity scene according to the activity information under each level value; evaluating a first user quantity of the participating user;
S102, calculating the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity;
s103, according to the reference signal receiving power data of the area where the activity scene is located, calculating a coverage value of the activity scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; acquiring a capacity value of a historical activity scene according to capacity index data of the activity scene;
s104, calculating an evaluation value of the activity scene according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and determining the wireless network grade of the activity scene based on the evaluation value, wherein the wireless network grade of different grades corresponds to different evaluation value intervals.
The present embodiment is exemplarily described with reference to a specific application scenario: wireless network assessment may be used for the grading of network guarantees under various types of activity scenarios, which may include meeting-type scenarios, conference-type scenarios, large public activities, etc. To achieve wireless network assessment, parameters for network assessment need to be determined and modeled, which may typically include user level, activity level, field test data, historical data.
One possible implementation is that, by using the first user value, the first level value and the first user quantity, a comprehensive value for reflecting the user level and the activity level can be obtained, and by using the comprehensive value and the coverage value, the quality value and the capacity value capable of reflecting the field test data, an evaluation value of the wireless network can be obtained, and the evaluation value and the occurrence frequency are comprehensively considered.
In connection with the scene example: firstly, 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 the activity scene according to the activity information under each level value; and evaluating a first user quantity of the participating users.
The first user value may be used to reflect a user level, and the user value may be divided into different intervals according to a certain criterion, the different intervals reflecting the user level. For example, the interval can be divided into four intervals of I, II, III and IV, wherein the interval I represents that the user is a provincial leader or a provincial company manager and above; the interval II indicates that the user is a city level leader or a city company manager level or more and is a provincial level leader or a provincial company manager level or less; section III indicates that the user is at or above the county level leader or the county company manager level and is at or below the city level leader or the city company manager level; section IV represents that the user is a county level leader or below a county company manager level, and four sections are set to correspond to different user values V respectively i In practical applications, the sum of the user values may be set to 10, and the higher the user level is, the higher the corresponding user value is.
The first level value may be used to reflect the level of the sponsor of the campaign, and generally, the higher the sponsor level, the greater the degree of assurance required. Specifically, the activity level refers to a level of an activity sponsor, and if there are multiple sponsors in a meeting, the sponsor of the highest level is used as the reference. The activity level can be classified into international level, national level, provincial level, municipal level, district level, county level and the like from high to low, specifically, let f (alpha) be an activity level value, and when the activity level is not lower than the national level, the activity level value can be made to be 3; when the activity level is lower than the ground city level, the activity level value can be made to be 1; an activity level of 2 may be made when the activity level is not lower than the city level but lower than the country level.
The first user quantity is used for evaluating the number scale of the event, wherein the number scale refers to the number of participants in the event of gathering, and the maximum number of users and the user participation factor can be accommodated in the event of gathering by comprehensively considering the factors of the event, and can be calculated by N=Kx. Wherein N represents the number of people on the activity site, K represents the participation rate of users, K is more than 0 and less than or equal to 1, and x represents the maximum number of users which can be accommodated on the activity site.
An example, S102 may specifically include:
based on a first formula, a composite value P of the activity scene is calculated.
Wherein the first formula comprises:
wherein V is i For the i 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.
The present embodiment provides a feasible integrated value calculation method. In the first formula, the first level value is assigned according to the highest-level sponsor unit; in the first user value, the user group existing in the active scene is taken to calculate the user value, for example, if no user of the interval I exists in the current active scene, the user value corresponding to the interval I does not need to be summed; the first user quantity is reflected in the form of an order of magnitude, and the order of magnitude of the first user quantity can be obtained by taking the logarithm of the user quantity based on 10.
The integrated value is obtained according to the first user value, the first level value and the first user quantity, and can comprehensively reflect the level of the participating user, the activity level and the activity scale, namely the basic attribute of the one-field activity. Moreover, only the order of magnitude of the highest-level sponsor units, the user values participating in the activities and the total user quantity is considered, so that the calculation can be greatly simplified, the use efficiency is improved, and the basic condition of the activities can be reflected more accurately.
After the comprehensive value is obtained, a series of auxiliary indexes are needed for comprehensive assessment of the grade, and one possible implementation mode is to use field test data for assessment, and if the field test data cannot be obtained, simulation estimation can be carried out according to similar scene historical data. Specifically, according to the reference signal receiving power data of the area where the active scene is located, calculating the coverage value of the active scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; and acquiring the capacity value of the activity scene according to the capacity index data of the historical activity scene. The coverage value and the quality value can reflect the signal quality in the active scene, and the capacity value can be used for carrying out simulation prediction on the current scene according to the data of the historical similar scene.
Finally, the evaluation value of the activity scene can be calculated according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and the wireless network level of the activity scene is determined based on the evaluation value, wherein the wireless network levels of different levels correspond to different evaluation value intervals. The interval to which the evaluation value M belongs can be divided according to actual situations, and in practical application, a feasible dividing point selection manner is to divide an initial level into four intervals by taking 17.8, 11.12 and 6.08 as boundaries, wherein the initial level is defined as an initial level S when M is not less than 17.8, is defined as an initial level a when M is less than 17.8 but not less than 11.12, is defined as an initial level B when M is less than 11.12 but not less than 6.08, and is defined as an initial level C when M is less than 6.08.
The embodiment provides a wireless network evaluation method, which obtains a comprehensive value of an activity scene according to a user value, a user quantity and a level value of the activity scene of a participating user, calculates a coverage value and a quality value of the activity scene based on communication data of an area where the activity scene is located, and determines a wireless network level of the activity scene by combining a 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.
Example two
Fig. 3 is a flow chart of a wireless network evaluation method provided in the second embodiment of the present application, which is used for illustrating a process of calculating an evaluation value of an active scene according to a comprehensive value, a coverage value, a quality value and a capacity value of the active scene, and determining a wireless network level of the active scene based on the evaluation value, as shown in fig. 3, on the basis of any embodiment, S104 may specifically include:
s201, calculating and obtaining an evaluation value M of the activity scene based on a second formula.
Wherein the second formula comprises: m=p×ω 1 +C×ω 2 +Q×ω 3 +L×ω 4
Wherein P is a comprehensive value; c is a coverage value; q is a mass value; l is a capacity value; omega 1 The weight coefficient is the integrated value; omega 2 A weight coefficient that is a coverage value; omega 3 Weight coefficients for the mass values; omega 4 A weight coefficient for the capacity value; wherein omega 1 +ω 2 +ω 3 +ω 4 ＝1；
S202, according to the evaluation value of the activity scene, determining the wireless network level of the activity scene based on the evaluation value intervals corresponding to different wireless network levels.
The present embodiment is exemplarily described with reference to a specific application scenario: the second formula is a weighted average, and the comprehensive value, the coverage value, the quality value and the capacity value are given different weights to obtain an evaluation value. The respective weight coefficients are not particularly limited in general, but may be set according to actual conditions. By way of example, the ω 1 To omega 4 The values of (2) may be 0.4, 0.2, i.e. the composite value is given a relatively large weight. Meter with a meter bodyAfter the evaluation value is calculated, the corresponding initial grade may be obtained according to the implementation of the initial grade division described in the first embodiment.
In an example, in S103, the calculating the coverage value of the active scene according to the reference signal received power data of the area where the active scene is located specifically includes:
according to the reference signal received power data of the area where the active scene is located, obtaining a first proportion of the position points of which the reference signal received power data is not lower than a preset power threshold value in the position points of the area;
Based on a third formula, calculating and obtaining a coverage value C of the activity scene: c=100× (1-r); wherein r is the first ratio.
Specifically, the reference signal received power (Reference Signal Receiving Power, RSRP for short) refers to the average value of the power received on all the resource elements carrying the reference signal in a certain symbol, and is an important index for measuring the coverage rate of the network. The RSRP values of the location points in the active scenario can be extracted on the monitoring result (Measurement Result, MR for short) data platform, and a threshold value, for example-110 dBm, needs to be set for the values. Counting the ratio of RSRP more than or equal to-110 dBm, setting the ratio as r, and obtaining the corresponding coverage value C under different ratios through C=100× (1-r).
The coverage value C represents the network coverage rate in the active scene in a proportional form through the statistics of the environmental measurement value of the reference signal received power, and the description of the network coverage condition is simplified.
In yet another example, in S103, the calculating the quality value of the active scene according to the signal-to-noise ratio data of the area where the active scene is located specifically includes:
obtaining second proportions of the position points of which the signal to noise ratio data is not lower than a preset gain threshold value in each position point of the region according to the signal to noise ratio data of the region where the active scene is located;
Based on a fourth formula, calculating and obtaining a quality value Q of the activity scene: q=100× (1-Q); wherein q is the second ratio.
Signal to noise ratio (Signal to Interference plus Noise Ratio, SINR) data is defined as the ratio of the received useful signal strength to the interfering signal strength, reflecting the relative magnitude of the useful signal. The signal-to-noise ratio can also be obtained by an MR data platform, and the signal-to-noise ratio value of each position point in the active scene is obtained in the platform. It is also necessary to set a threshold value for this value, for example 0dB. The ratio of SINR not less than 0dB is counted, the ratio is set to Q, and the corresponding quality value Q under different ratios can be obtained through Q=100× (1-Q).
Similar to the previous embodiment, the quality value Q scales the signal quality in a proportional manner, simplifying the description of the signal quality case.
In another example, in S103, the acquiring the capacity value of the activity scene according to the capacity index data of the historical activity scene specifically includes:
acquiring the maximum number of users of the activity scenes with the same type of history, wherein the maximum number of users is obtained by calculating index parameters in an activity period based on a cell in which the activity scenes with the same type of history are located; wherein the index parameter includes at least one of: resource utilization rate of a busy downlink channel PRB and RRC connection;
Calculating the average number of the maximum users of the activity scenes with the same type of history, and calculating the cell number C1 of the activity scenes based on a fifth formula:
wherein beta is a preset user occupancy, N is the first user quantity, < + >>
The average number of users;
based on a sixth formula, calculating and obtaining a capacity value L of the activity scene: l=100× (C 1 -C 2 )/C 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein C is 2 And the number of the network cells in the activity scene.
The evaluation of the capacity requirement of the activity scene can be calculated through the capacity index of the activity scene of the historical same type. Specifically, first, a similar activity scene is selected, where the activity scene may include a singing concert, a sports event, a release concert, an exhibition, etc., and the selection is performed according to the actual activity scene to be applied. And secondly, extracting capacity indexes of the similar gathering activity scene occupied cell in the last historical activity time period, wherein the capacity indexes comprise the resource utilization rate of a downlink channel PRB when the cell is busy, the maximum number of users established by RRC connection, the downlink cell flow and the like. Finally, a capacity value L of the gathering activity is calculated according to the capacity index.
Illustratively, taking the example of using the resource utilization of the PRB of the busy downlink channel in combination with the RRC connection, it may specifically be:
(1) And extracting the busy hour downlink channel PRB resource utilization rate and the RRC connection establishment maximum user number index of the similar activity scene occupation cell in the last historical activity time period in the unified network element management system, wherein the busy hour statistics are set to be the maximum value of the busy hour.
(2) According to the extracted index value, the resource utilization rate of the downlink channel PRB in busy hour is screened to be 80 percent and 85 percent]The cell between the two cells obtains the maximum number of RRC connection establishment corresponding to each record, and the maximum number is recorded as RRC 1 、RRC 2 …RRC n . Therefore, the average value of the maximum number of RRC connection setup users
The method comprises the following steps:
wherein n is the number of data records,
the whole number is retained according to rounding.
(3) Establishing a maximum user number average value according to the first user quantity N and RRC connection
Estimating the number of cells C meeting the capacity requirement of an active site 1 The calculation method is as follows: />
Wherein beta is the market share of users of a certain operator, and beta reserves two decimal places according to rounding method, C 1 The whole number is retained according to rounding.
(4) Counting the number C of network cells in the current activity scene in a unified network element management system 2 Calculate the capacity value of the activity L: l=100× (C 1 -C 2 )/C 1
Wherein L is retained to integer digits according to rounding.
According to the method, the relation between the activity scenes of the same type and the activity scene to be evaluated is constructed, and analysis modeling is carried out on each index of the activity scenes of the same type by means of at least one index in the resource utilization rate of the PRB and the RRC connection of the busy downlink channel, so that a simple method for expressing the capacity requirement of the activity scenes is obtained.
The three embodiments for calculating the coverage value, the quality value, and the capacity value may be implemented alone or in combination.
In this embodiment, a weighted average formula is used, and an evaluation value of the active scene is obtained through calculation of a comprehensive value, a coverage value, a quality value and a capacity value, and according to the evaluation value of the active scene, wireless network levels of the active scene are determined based on evaluation value intervals corresponding to different wireless network levels. By the embodiment, the indexes can be conveniently calculated, and the wireless network evaluation level of the activity scene can be quantified in the mode of evaluation values and intervals thereof.
Example III
Fig. 4 is a schematic flow chart of a wireless network evaluation method provided in the third embodiment of the present application, as shown in fig. 4, where on the basis of any embodiment, the method further includes:
S301, determining the occurrence frequency type of the activity scene, wherein the occurrence frequency type comprises a burst type and a long-term type;
s311, if the occurrence frequency type of the active scene is a burst type, adjusting the wireless network level of the active scene to be a wireless network level of a higher level;
and S310, if the occurrence frequency type of the activity scene is a long-term type, not executing wireless network level adjustment.
The present embodiment is exemplarily described with reference to a specific application scenario: the occurrence frequency types of the activity scene can comprise burst type and long-term type, and for the burst type, the wireless network grade assessment is improved so as to increase the network guarantee strength of the activity scene; and for the long-term type, the initial grade is directly used as the grade, and corresponding grade evaluation and matched service are carried out according to the calculation result of the evaluation value. Specifically, if the occurrence frequency is determined to be of a long-term type, the scene is divided into S, A, B, C levels according to the calculated evaluation value directly and according to the size thereof, and correspondingly, if the occurrence frequency of S, A, B, C levels is of a burst type, the scene is divided into s+ and S, A, B levels.
Taking Q-exposition activity as an example, the method is employed for wireless network assessment. Firstly, determining a user value V according to a showuser i = {4,3,2,1}, activity level value f (α) = 2 is determined from the sponsor unit level, n=600000 is determined from the number of live persons of the activity, and the integrated value p=17.78 is obtained by calculation.
Secondly, SINR data of a exhibition center A are extracted from an MR data platform, the ratio r of RSRP more than or equal to-110 dBm is calculated to be 100%, and a coverage value C=0 can be obtained through calculation; SINR data of the museum A are extracted from the MR data platform, the proportion q of SINR not less than 0dB is 97.08%, and the mass value q=2.92 is obtained through calculation.
Thirdly, under a certain fixed time period, the unified network element management system extracts the daily busy downlink channel PRB resource utilization rate and the RRC connection of all cells of the convention center to establish the maximum user number index, and the daily busy downlink channel PRB resource utilization rate is [80 percent ] through screening,85％]the cells in between average the corresponding maximum number of RRC connection establishment users to obtain the average value of the maximum number of RRC connection establishment users
Calculating to obtain the cell number C meeting the capacity requirement of the activity site 1 =98, counting the number of cells in the network C in the unified network element management system 2 =73, thereby calculating the capacity value l=26.
Finally, calculating the M value of the current activity: m=p×0.4+c×0.2+q×0.2+l×0.2= 12.896, and the initial rank a can be obtained by comparison. Since the exposition activities are annual, i.e. the frequency of occurrence type should be of a long-term type, the end result of the wireless network evaluation is that the activity scenario network level is level a, and correspondingly, a network guarantee with a strength of level a should be performed.
In this embodiment, first, determining an occurrence frequency type of the activity scene, where the occurrence frequency type includes a burst type and a long-term type; if the occurrence frequency type of the active scene is a burst type, adjusting the wireless network level of the active scene to be a wireless network level of a higher level; if the occurrence frequency type of the activity scene is a long-term type, wireless network level adjustment is not performed. According to whether the activity scene is an emergency or not, whether the network evaluation level should be improved or not is determined, and the reliability of wireless network evaluation is improved.
Example IV
The fourth embodiment of the present application further provides an image recognition device to implement the foregoing method. As shown in fig. 5, fig. 5 is a schematic structural diagram of a wireless network evaluation device according to a fourth embodiment of the present application, where the device includes:
A determining module 41, configured to determine a first user value corresponding to the participating user according to the user information under each user value; determining a first level value corresponding to the activity scene according to the activity information under each level value; evaluating a first user quantity of the participating user;
a calculation module 42, 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; according to the reference signal receiving power data of the area where the active scene is located, calculating the coverage value of the active scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; acquiring a capacity value of a historical activity scene according to capacity index data of the activity scene;
and the evaluation module 43 is configured to calculate an evaluation value of the activity scene according to the integrated value, the coverage value, the quality value and the capacity value of the activity scene, and determine a wireless network level of the activity scene based on the evaluation value, where the wireless network levels of different levels correspond to different evaluation value intervals.
The present embodiment is exemplarily described with reference to a specific application scenario: the determining module 41 obtains the user value, the user quantity and the level value of the activity scene of the participating user; the calculation module 42 calculates the comprehensive value of the activity scene according to the data obtained by the determination module 41, calculates the coverage value and the 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 condition of the similar scene; the evaluation module 43 performs weighted average according to the data calculated by the calculation module 42, calculates an evaluation value of the activity scene, and determines a wireless network level of the activity scene according to the evaluation value and the evaluation value interval divided in advance.
The calculation module 42 is specifically configured to calculate the integrated value P of the activity scene based on a first formula, for example.
Wherein the first formula comprises:
wherein V is i For the i 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 computing module may specifically obtain a comprehensive value according to the first user value, the first level value and the first user quantity, so as to comprehensively reflect the level of the participating user, the activity level and the activity scale, that is, the basic attribute of the first activity. Moreover, only the order of magnitude of the highest-level sponsor units, the user values participating in the activities and the total user quantity is considered, so that the calculation can be greatly simplified, the use efficiency is improved, and the basic condition of the activities can be reflected more accurately.
An example, the evaluation module 43 is specifically configured to:
based on a second formula, an evaluation value M of the activity scene is calculated and obtained.
Wherein the second formula comprises: m=p×ω 1 +C×ω 2 +Q×ω 3 +L×ω 4
Wherein P is a comprehensive value; c is a coverage value; q is a mass value; l is a capacity value; omega 1 The weight coefficient is the integrated value; omega 2 A weight coefficient that is a coverage value; omega 3 Weight coefficients for the mass values; omega 4 A weight coefficient for the capacity value; wherein omega 1 +ω 2 +ω 3 ω 4 ＝1；
The evaluation module 43 is further configured to determine, according to the evaluation value of the activity scene, a wireless network level of the activity scene based on evaluation value intervals corresponding to different wireless network levels.
In this embodiment, the evaluation module performs weighted average on the integrated value, the coverage value, the quality value, and the capacity value, calculates to obtain an evaluation value of the activity scene, and determines, according to the evaluation value of the activity scene, a wireless network level of the activity scene based on evaluation value intervals corresponding to different wireless network levels. This embodiment 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.
As an example, the computing module 42 may be specifically configured to:
according to the reference signal received power data of the area where the active scene is located, obtaining a first proportion of the position points of which the reference signal received power data is not lower than a preset power threshold value in the position points of the area;
based on a third formula, calculating and obtaining a coverage value C of the activity scene: c=100× (1-r); wherein r is the first ratio.
In this embodiment, RSRP is used to measure network coverage, and RSRP values of each location point in an active scenario may be extracted on the MR data platform. The calculation module 42 may count the proportion that RSRP is not lower than the predetermined threshold, set the proportion to r, and derive the corresponding coverage value C at the different proportions by c=100× (1-r). The coverage value C represents the network coverage rate in the active scene in a proportional form through the statistics of the environmental measurement value of the reference signal received power, and the description of the network coverage condition is simplified.
As yet another example, the computing module 42 may also be specifically configured to:
obtaining second proportions of the position points of which the signal to noise ratio data is not lower than a preset gain threshold value in each position point of the region according to the signal to noise ratio data of the region where the active scene is located;
based on a fourth formula, calculating and obtaining a quality value Q of the activity scene: q=100× (1-Q); wherein q is the second ratio.
In this embodiment, the signal-to-noise ratio may reflect the relative magnitude of the effective signal, or may obtain the signal-to-noise ratio value of each position point in the active scene through the MR data platform. The calculation module 42 may count the proportion of SINR not lower than the predetermined threshold, set the proportion to Q, and derive the corresponding quality value Q at different proportions by q=100× (1-Q). The quality value Q scales the signal quality in a proportional manner, simplifying the description of the signal quality situation.
As another example, the calculating module 42 is specifically configured to obtain, according to the capacity index data of the historical activity scenario, a capacity value of the activity scenario, and specifically includes:
the calculation module 42 is specifically further configured to obtain a maximum number of users of the activity scenes of the same type, where the maximum number of users is obtained by calculating index parameters in an activity period based on a cell in which the activity scenes of the same type are located; wherein the index parameter includes at least one of: resource utilization rate of a busy downlink channel PRB and RRC connection;
the calculating module 42 is specifically further configured to calculateAverage number of maximum number of users of the activity scenes with the same historical type, and calculating and obtaining cell number C of the activity scenes based on a fifth formula 1 ：
Wherein beta is a preset user occupancy, N is the first user quantity, < + >>
The average number of users; />
The calculating module 42 is specifically further configured to calculate and obtain the capacity value L of the activity scene based on a sixth formula: l=100× (C 1 -C 2 )/C 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein C is 2 And the number of the network cells in the activity scene.
In this embodiment, the calculation module 42 performs analysis modeling on each index of the activity scene of the same type by constructing a relationship between the activity scene of the same type and the activity scene to be evaluated, and by using at least one index of the resource utilization rate of the PRB of the busy downlink channel and the RRC connection, a simple method for expressing the capacity requirement of the activity scene is obtained.
An example, the apparatus further comprises a frequency of occurrence identification module, in particular for:
determining the occurrence frequency type of the activity scene, wherein the occurrence frequency type comprises a burst type and a long-term type;
the occurrence frequency identification module is further used for adjusting the wireless network grade of the active scene to be a wireless network grade of a higher grade if the occurrence frequency type of the active scene is a burst type; if the occurrence frequency type of the activity scene is a long-term type, wireless network level adjustment is not performed.
In this embodiment, the occurrence frequency identification module first determines an occurrence frequency type of the active scene, including a burst type and a long-term type; if the occurrence frequency type of the active scene is a burst type, the occurrence frequency identification module adjusts the wireless network level of the active scene to be a wireless network level of a higher level; if the occurrence frequency type of the activity scene is a long-term type, 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 or not, so that the reliability of wireless network evaluation is improved.
The embodiment provides a wireless network evaluation device, wherein a determining module acquires a user value, a user quantity and a level value of an activity scene of a participating user; the calculation module calculates the comprehensive value of the activity scene according to the index acquired by the determination module, calculates the coverage value and the quality value of the activity scene based on the communication data of the area where the activity scene is located, and acquires the capacity value of the activity scene according to the historical similar scene data; the evaluation module performs weighted average on the indexes obtained by the calculation module to determine the wireless network level of the activity scene. The device can be used for comprehensively analyzing multiple parameters such as user level, activity level, people number scale, event time, network coverage, network quality, network capacity and the like, and conveniently realizes wireless network evaluation.
Example five
Fig. 6 is a schematic structural diagram of an electronic device provided in a fifth embodiment of the present application, as shown in fig. 6, where the electronic device includes:
a processor 291, the electronic device further comprising a memory 292; a communication interface (Communication Interface) 293 and bus 294 may also be included. The processor 291, the memory 292, and the communication interface 293 may communicate with each other via the bus 294. Communication interface 293 may be used for information transfer. The processor 291 may call logic instructions in the memory 294 to perform the methods of the above embodiments.
Further, the logic instructions in memory 292 described above may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product.
The memory 292 is a computer readable storage medium, and may be used to store a software program, a computer executable program, and 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 software programs, instructions and modules stored in the memory 292, i.e., implements the methods of the method embodiments described above.
Embodiments of the present application also provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, are configured to implement the method described in any of the embodiments.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the present application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (16)
1. A wireless network evaluation method, comprising:
determining a first user value corresponding to the participating user according to the user information under each user value; determining a first level value corresponding to the activity scene according to the activity information under each level value; evaluating a first user quantity of the participating user;
calculating the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; according to the reference signal receiving power data of the area where the active scene is located, calculating the coverage value of the active scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; acquiring a capacity value of a historical activity scene according to capacity index data of the activity scene;
And calculating an evaluation value of the activity scene according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and determining the wireless network grade of the activity scene based on the evaluation value, wherein the wireless network grade of different grades corresponds to different evaluation value intervals.
2. The method of claim 1, wherein calculating the composite value of the activity scene based on the first user value, the first level value, and the first user quantity comprises:
based on a first formula, calculating a comprehensive value P of the activity scene:
wherein V is i For the i 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 of claim 2, wherein the calculating the evaluation value of the activity scene from the integrated value, the coverage value, the quality value, and the capacity value of the activity scene, and determining the wireless network level of the activity scene based on the evaluation value, comprises:
based on a second formula, calculating and obtaining an evaluation value M of the activity scene:
M＝P×ω 1 +C×ω 2 +Q×ω 3 +L×ω 4
wherein P is a comprehensive value; c is a coverage value; q is a mass value; l is a capacity value; omega 1 The weight coefficient is the integrated value;ω 2 a weight coefficient that is a coverage value; omega 3 Weight coefficients for the mass values; omega 4 A weight coefficient for the capacity value; wherein omega 1 +ω 2 +ω 3 +ω 4 ＝1；
And determining the wireless network grade of the activity scene based on the evaluation value intervals corresponding to different wireless network grades according to the evaluation value of the activity scene.
4. The method according to claim 1, wherein the calculating the coverage value of the active scene according to the reference signal received power data of the area where the active scene is located comprises:
according to the reference signal received power data of the area where the active scene is located, obtaining a first proportion of the position points of which the reference signal received power data is not lower than a preset power threshold value in the position points of the area;
based on a third formula, calculating and obtaining a coverage value C of the activity scene: c=100× (1-r); wherein r is the first ratio.
5. The method according to claim 1, wherein calculating the quality value of the active scene according to the signal-to-noise ratio data of the area where the active scene is located comprises:
obtaining second proportions of the position points of which the signal to noise ratio data is not lower than a preset gain threshold value in each position point of the region according to the signal to noise ratio data of the region where the active scene is located;
Based on a fourth formula, calculating and obtaining a quality value Q of the activity scene: q=100× (1-Q); wherein q is the second ratio.
6. The method of claim 1, wherein the obtaining the capacity value of the activity scene from the capacity index data of the historical activity scene comprises:
acquiring the maximum number of users of the activity scenes with the same type of history, wherein the maximum number of users is obtained by calculating index parameters in an activity period based on a cell in which the activity scenes with the same type of history are located; wherein the index parameter includes at least one of: a busy downlink channel physical resource block (Physical Resource Block, PRB for short) resource utilization and radio resource control (Radio Resource Control, RRC for short) connection;
calculating the average number of the maximum number of users of the activity scenes with the same type of history, and calculating the cell number C of the activity scenes based on a fifth formula 1 ：
Wherein beta is a preset user occupancy, N is the first user quantity, < + >>
The average number of users;
based on a sixth formula, calculating and obtaining a capacity value L of the activity scene: l=100× (C 1 -C 2 )/C 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein C is 2 And the number of the network cells in the activity scene.
7. The method according to any one of claims 1-6, further comprising:
determining the occurrence frequency type of the activity scene, wherein the occurrence frequency type comprises a burst type and a long-term type;
if the occurrence frequency type of the active scene is a burst type, adjusting the wireless network level of the active scene to be a wireless network level of a higher level;
if the occurrence frequency type of the activity scene is a long-term type, wireless network level adjustment is not performed.
8. A wireless network evaluation apparatus, comprising:
the determining module is used for determining a first user value corresponding to the participating user according to the user information under each user value; determining a first level value corresponding to the activity scene according to the activity information under each level value; evaluating a first user quantity of the participating user;
the calculation module is used for calculating the comprehensive value of the activity scene according to the first user value, the first level value and the first user quantity; according to the reference signal receiving power data of the area where the active scene is located, calculating the coverage value of the active scene; calculating a quality value of the activity scene according to the signal-to-noise ratio data of the area where the activity scene is located; acquiring a capacity value of a historical activity scene according to capacity index data of the activity scene;
And the evaluation module is used for calculating an evaluation value of the activity scene according to the comprehensive value, the coverage value, the quality value and the capacity value of the activity scene, and determining the wireless network grade of the activity scene based on the evaluation value, wherein the wireless network grades of different grades correspond to different evaluation value intervals.
9. The apparatus of claim 8, wherein the device comprises a plurality of sensors,
the calculation module is specifically configured to calculate, based on a first formula, a comprehensive value P of the activity scene:
wherein V is i For the i 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 apparatus of claim 8, wherein the device comprises a plurality of sensors,
the evaluation module is specifically configured to calculate and obtain an 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 a comprehensive value; c is a coverage value; q is a mass value; l is a capacity value; omega 1 The weight coefficient is the integrated value; omega 2 A weight coefficient that is a coverage value;ω 3 weight coefficients for the mass values; omega 4 A weight coefficient for the capacity value; wherein omega 1 +ω 2 +ω 3 +ω 4 ＝1；
The evaluation module is specifically further configured to determine, according to the evaluation value of the activity scene, a wireless network level of the activity scene based on evaluation value intervals corresponding to different wireless network levels.
11. The apparatus of claim 8, wherein the device comprises a plurality of sensors,
the computing module is specifically configured to obtain, according to reference signal received power data of an area where an active scene is located, a first proportion of a location point whose reference signal received power data is not lower than a predetermined power threshold value in the location points of the area;
the calculating module is specifically further configured to calculate and obtain a coverage value C of the activity scene based on a third formula: c=100× (1-r); wherein r is the first ratio.
12. The apparatus of claim 8, wherein the device comprises a plurality of sensors,
the computing module is specifically configured to obtain, according to signal-to-noise ratio data of an area where the active scene is located, a second proportion of position points whose signal-to-noise ratio data is not lower than a predetermined gain threshold value in the position points of the area;
the calculating module is specifically further configured to calculate and obtain a quality value Q of the active scene based on a fourth formula: q=100× (1-Q); wherein q is the second ratio.
13. The apparatus of claim 8, wherein the device comprises a plurality of sensors,
the calculation module is specifically configured to obtain a capacity value of the activity scene according to capacity index data of the historical activity scene, and specifically includes:
The calculation module is specifically configured to obtain a maximum number of users of the same type of historical activity scenes, where the maximum number of users is obtained by calculating index parameters in an activity period based on a cell where the same type of historical activity scenes are located; wherein the index parameter includes at least one of: resource utilization rate of a busy downlink channel PRB and RRC connection;
the calculation module is specifically configured to calculate an average number of maximum users of the activity scenes of the same type, and calculate a cell number C of the activity scenes based on a fifth formula 1 ：
Wherein beta is a preset user occupancy, N is the first user quantity, < + >>
The average number of users;
the calculation module is specifically further configured to calculate and obtain a capacity value L of the activity scene based on a sixth formula: l=100× (C 1 -C 2 )/C 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein C is 2 And the number of the network cells in the activity scene.
14. The apparatus according to any one of claims 8-13, wherein the apparatus further comprises:
the occurrence frequency identification module is used for determining the occurrence frequency type of the activity scene, wherein the occurrence frequency type comprises a burst type and a long-term type;
the occurrence frequency identification module is further configured to adjust a wireless network level of the active scene to a wireless network level of a higher level if the occurrence frequency type of the active scene is a burst type; if the occurrence frequency type of the activity scene is a long-term type, wireless network level adjustment is not performed.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
16. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-7.
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