A network quality evaluation method and device, electronic equipment and storage medium

Abstract

The application provides a network quality evaluation method and device, electronic equipment and storage medium, relates to the technical field of communication, and is used for accurately evaluating the network quality of a target area. The method comprises the following steps: acquiring collection data, the collection data comprising a plurality of signal strength values obtained by collecting the signal strength of a terminal in the target area within a first time period; determining the statistical number of N signal strength intervals according to the collection data; the statistical number of the signal strength intervals is used to represent the number of signal strength values in the plurality of signal strength values located in the signal strength interval, and N is a positive integer greater than 1; determining the initial score of the network quality of the target area according to the statistical number of the N signal strength intervals; and in the case that the ratio of the first collection number to the second collection number is greater than or equal to a first preset ratio, punishing the initial score of the network quality to obtain the network quality score of the target area.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a network quality assessment method, apparatus, electronic device, and storage medium. Background Technology

[0002] Current technical methods for evaluating home network quality generally involve using wireless access points (APs), i.e., routers or optical modems with wireless fidelity (WiFi) capabilities, to collect the negotiation rate and received signal strength indicator (RSSI) of devices connected to their WiFi network. A simple arithmetic average is then used to calculate the network quality assessment for each AP. However, this method only evaluates the signal strength of devices connected to a single AP. In reality, there may be multiple APs within a home, making it impossible to accurately determine the home network quality score. Therefore, a more precise method for evaluating network quality is urgently needed. Summary of the Invention

[0003] This invention provides a network quality assessment method, apparatus, electronic device, and storage medium for accurately assessing the network quality of a target area. The technical solution of this invention is as follows:

[0004] In a first aspect, the present invention provides a network quality assessment method, the method comprising: acquiring collected data, the collected data including multiple signal strength values ​​obtained by collecting signal strength of terminals in a target area within a first time period; determining the statistical frequency of N signal strength intervals based on the collected data; the statistical frequency of the signal strength interval is used to characterize the number of signal strength values ​​in the multiple signal strength values ​​that are located in the signal strength interval, where N is a positive integer greater than 1; determining an initial network quality score for the target area based on the statistical frequency of the N signal strength intervals; and penalizing the initial network quality score to obtain a network quality score for the target area when the ratio of the first number of collections to the second number of collections is greater than or equal to a first preset ratio, wherein the first number of collections is the number of signal strength values ​​less than a first threshold among the multiple signal strength values, and the second number of collections is the number of signal strength values ​​included in the collected data.

[0005] The technical solution provided by this invention offers at least the following beneficial effects: Compared to existing technologies that assess network quality in the area covered by an AP (router or optical modem with WiFi capability) by collecting signal strength data from devices connected to the AP, this invention assesses network quality in a target area by collecting multiple signal strength values ​​from terminals within that area. Furthermore, by analyzing the distribution of these multiple signal strength values ​​within the target area (i.e., the statistical frequency of N signal strength intervals), an initial network quality score for the target area can be accurately determined. On this basis, when the ratio of the first number of collected signals to the second number of collected signals is greater than or equal to a first preset ratio (i.e., when lower signal strength values ​​occur more frequently in the target area), a penalty is applied to the initial network quality score, making the penalized score more closely reflect user experience. Therefore, the embodiments of this invention improve the accuracy of network quality assessment in target areas.

[0006] In one possible implementation, N signal strength intervals are arranged in descending order of statistical frequency to obtain an arrangement order of N signal strength intervals; the first M signal strength intervals are selected from the arrangement order, where the ratio between the sum of the statistical frequencies of the first M signal strength intervals in the arrangement order and the second number of samples is greater than or equal to a second preset ratio, and the ratio between the sum of the statistical frequencies of the first M-1 signal strength intervals in the arrangement order and the second number of samples is less than the second preset ratio, where M is a positive integer; the average value of the midpoints of the first M signal strength intervals in the arrangement order is calculated; based on the average value of the midpoints, the upper limit and lower limit of the signal strength interval to which the average value of the midpoints belong, the initial network quality score of the target area is determined.

[0007] Based on this possible implementation, the N signal strength intervals are arranged in descending order of statistical frequency, resulting in a sorted order of the N signal strength intervals. The initial network quality score for the target area is determined by selecting the first M signal strength intervals from this sorted order. This can improve the efficiency of evaluating the network quality of the target area.

[0008] In another possible implementation, the initial network quality score of the target area satisfies the following relationship:

[0009] V = (E-Di) / (Ui-Di)*t + Ai

[0010] Where V is the initial network quality score, E is the average of the group midpoints, Di is the lower limit of the signal strength interval to which the average of the group midpoints belongs, Ui is the upper limit of the signal strength interval to which the average of the group midpoints belongs, t is the adjustment coefficient, and Ai is the reference score corresponding to the average of the group midpoints.

[0011] Based on this possible implementation, the group midpoint represents the average signal strength level of its corresponding signal strength interval. A more comprehensive and effective initial score for the network quality of the target area is determined by combining the average of the group midpoints, the upper limit of the signal strength interval to which the average of the group midpoints belongs, and the lower limit, thereby making the subsequent network quality scores for the target area more accurate.

[0012] In another possible implementation, if the ratio of the third number of samples to the second number of samples is greater than or equal to a third preset ratio, the initial network quality score is set to a preset value, and the third number of samples is the number of signal strength values ​​that are greater than or equal to a second threshold among multiple signal strength values.

[0013] Based on this possible implementation, if the ratio of the number of signal strength values ​​greater than or equal to the second threshold to the second number of samples is greater than or equal to the third preset ratio, the initial network quality score is set to a preset value, simplifying the operation and improving the evaluation efficiency of network quality in the target area.

[0014] In another possible implementation, the first time period includes one or more target sub-time periods within the second time period, and the ratio of the number of terminals connected to the wireless network in the target area within the target sub-time period to the preset maximum number of terminals exceeds a fourth preset ratio.

[0015] Based on this possible implementation method, the first time period is selected as the target sub-time period where the ratio of the number of terminals in the target area's wireless network to the preset maximum number of terminals exceeds a fourth preset ratio. The first time period is the valid time, and the statistical count within this time period is closer to reality, so that the subsequent network quality score of the target area is more accurate and realistic.

[0016] In a second aspect, the present invention provides a network quality assessment device, the device comprising: an acquisition module for acquiring collected data, the collected data including multiple signal strength values ​​obtained by acquiring the signal strength of terminals in a target area within a first time period;

[0017] The processing module is used to determine the statistical frequency of N signal strength intervals based on the collected data; the statistical frequency of the signal strength interval is used to characterize the number of signal strength values ​​that fall within the signal strength interval among multiple signal strength values, where N is a positive integer greater than 1;

[0018] The processing module is also used to determine the initial network quality score of the target area based on the statistical frequency of N signal strength intervals;

[0019] The processing module is also used to penalize the initial network quality score when the ratio of the first number of samples to the second number of samples is greater than or equal to the first preset ratio, so as to obtain the network quality score of the target area. The first number of samples is the number of signal strength values ​​less than the first threshold among multiple signal strength values, and the second number of samples is the number of signal strength values ​​included in the sampled data.

[0020] In one possible implementation, the processing module is specifically used for:

[0021] Arrange the N signal intensity intervals in descending order of their statistical frequency to obtain the order of the N signal intensity intervals;

[0022] Select the first M signal strength intervals from the arrangement order. The ratio between the sum of the statistical counts of the first M signal strength intervals in the arrangement order and the second number of samples is greater than or equal to the second preset ratio, and the ratio between the sum of the statistical counts of the first M-1 signal strength intervals in the arrangement order and the second number of samples is less than the second preset ratio. M is a positive integer.

[0023] Calculate the average of the midpoints of the first M signal intensity intervals in the sorted order;

[0024] The initial network quality score for the target area is determined based on the average value of the group midpoint, the upper limit and lower limit of the signal strength interval to which the average value of the group midpoint belongs.

[0025] In another possible implementation, the initial network quality score of the target area satisfies the following relationship:

[0026] V = (E-Di) / (Ui-Di)*t + Ai

[0027] Where V is the initial network quality score, E is the average of the group midpoints, Di is the lower limit of the signal strength interval to which the average of the group midpoints belongs, Ui is the upper limit of the signal strength interval to which the average of the group midpoints belongs, t is the adjustment coefficient, and Ai is the reference score corresponding to the average of the group midpoints.

[0028] In another possible implementation, the processing module is specifically used to: set the initial network quality score to a preset value when the ratio of the third number of samples to the second number of samples is greater than or equal to a third preset ratio, wherein the third number of samples is the number of signal strength values ​​greater than or equal to a second threshold among multiple signal strength values.

[0029] In another possible implementation, the first time period includes one or more target sub-time periods within the second time period, and the ratio of the number of terminals connected to the wireless network in the target area within the target sub-time period to the preset maximum number of terminals exceeds a fourth preset ratio.

[0030] Thirdly, the present invention also provides an electronic device comprising: a processor and a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions such that the electronic device performs a network quality assessment method as described in the first aspect and any possible implementation thereof.

[0031] Fourthly, the present invention also provides a computer-readable storage medium storing computer instructions that, when executed on an electronic device, cause the electronic device to perform a network quality assessment method as described in the first aspect and any possible implementation thereof. Attached Figure Description

[0032] Figure 1 A schematic diagram of a communication system provided in an embodiment of the present invention;

[0033] Figure 2 A flowchart of a network quality assessment method provided in this embodiment of the invention. Figure 1 ;

[0034] Figure 3 A flowchart of a network quality assessment method provided in this embodiment of the invention. Figure 2 ;

[0035] Figure 4 This is a schematic diagram of the structure of a network quality assessment device provided in an embodiment of the present invention;

[0036] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Wireless networks are widely used in people's daily work and life, but existing wireless routers have limited network transmission distance, and due to transmission distance and the influence of walls or obstacles, the network signal is weak or unstable. This is especially true for users with large houses and complex building layouts, who may have multiple wireless access points inside their homes to ensure good WIFI coverage in every corner.

[0039] To optimize the deployment of wireless networks within a region and ensure the normal, secure, and efficient operation of telecommunications networks and services, existing methods involve assessing the network quality in different areas and then adaptively improving and maintaining the network quality in those areas based on the assessment results. This ensures high availability of the entire communication service while simultaneously optimizing the system architecture to enhance deployment efficiency.

[0040] Currently, the main method for evaluating network quality in different areas is to collect the negotiation rate and signal strength (RSSI) of connected Wi-Fi devices through wireless access points (routers or optical modems with Wi-Fi capabilities). The network quality of different access points is then calculated using a simple arithmetic average. This method does not consider user handling of abnormal situations, and the simple arithmetic average cannot reflect user satisfaction with the network quality of the target area. Furthermore, the current evaluation method only assesses the signal strength of devices connected to a single access point. In real-world scenarios, there may be multiple access points within a home, making it impossible to accurately assess the network quality within the home.

[0041] In view of this, the present invention provides a network quality assessment method, which obtains multiple signal strength values ​​by collecting signal strength data within a target area during a first time period; determines the statistical frequency of N signal strength intervals based on the multiple signal strength values; determines an initial network quality score for the target area based on the statistical frequency of the N signal strength intervals; and finally, penalizes the initial network quality score if the ratio of the first number of data collected to the second number of data collected is greater than or equal to a first preset ratio, thereby accurately quantifying and assessing the network quality of the target area and achieving precise granularity of network quality assessment within the target area.

[0042] The technical solutions provided in this invention can be applied to home WiFi scenarios.

[0043] For example, Figure 1 The image below is a schematic diagram of a home communication system according to an embodiment of the present invention. The communication system may include an AC router 11, one or more wireless access points 12, and one or more terminals 13. The wireless access points 12 can communicate with the one or more terminals 13. The AC router refers to a router based on the 802.11AC wireless standard.

[0044] The wireless access point 12 can be used to implement functions such as terminal resource scheduling, wireless resource management, and wireless access control. Specifically, the wireless access point can be a panel wireless AP or an optical modem with WiFi functionality.

[0045] Terminal 13 can also be referred to as terminal equipment, user equipment, mobile station, mobile terminal, etc. For example, the terminal can be a mobile phone, tablet computer, computer with wireless transceiver capabilities, virtual reality terminal, augmented reality terminal, wireless terminal in industrial control, wireless terminal in autonomous driving, wireless terminal in remote surgery, wireless terminal in transportation safety, wireless terminal in smart cities, wireless terminal in smart homes, etc. The embodiments of the present invention do not limit the specific device form used for the terminal.

[0046] It should be noted that, Figure 1 This is just an example framework diagram. Figure 1 The number of devices included and the names of each device are unlimited.

[0047] The application scenarios of the embodiments of the present invention are not limited. The system architecture and business scenarios described in the embodiments of the present invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0048] The network quality assessment method provided by the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0049] Figure 2 This is a flowchart illustrating a network quality assessment method provided in an embodiment of the present invention. Figure 2 As shown, the method includes the following steps:

[0050] S101. Acquire collected data.

[0051] The collected data includes multiple signal strength values ​​obtained by collecting the signal strength of terminals in the target area during the first time period.

[0052] In some embodiments, the first time period includes one or more target sub-time periods within the second time period, wherein the ratio of the number of terminals connected to the wireless network in the target area to a preset maximum number of terminals within the target sub-time period exceeds a fourth preset ratio. For example, if the second time period is one week, then the first time period is the period within one week during which the ratio of the number of terminals connected to the wireless network in the target area to the preset maximum number of terminals exceeds the fourth preset ratio. For example, if the fourth preset ratio is 80%, the first time period is from 20:00 to 22:00 every day within one week.

[0053] In some embodiments, the signal strength of terminals within the target area is periodically collected during a first time period to obtain multiple signal strength values. For example, the signal strength of terminals within the target area is collected once every hour during the first time period to obtain multiple signal strength values.

[0054] In some embodiments, multiple signal strength values ​​within a target area can be acquired first; then, based on preset rules and the multiple signal strength values ​​within the target area, a preset number of signal strength values ​​are selected from the multiple signal strength values, and these preset number of signal strength values ​​are packaged into collected data. In this way, by first excluding some random data from multiple signal strength values ​​based on preset rules, the accuracy of the assessment of network quality in the target area can be improved.

[0055] For example, multiple signal strengths within a target area are acquired within a first time period. The minimum and maximum signal strength values ​​within the target area within the first time period are removed, and the remaining signal strength values ​​are encapsulated and converted to form the acquired data.

[0056] S102. Based on the collected data, determine the statistical frequency of N signal strength intervals.

[0057] The statistical frequency of the signal strength interval is used to characterize the number of signal strength values ​​that fall within the signal strength interval among multiple signal strength values, where N is a positive integer greater than 1.

[0058] For example, Table 1 is a statistical table showing the number of times the signal strength ranges are counted and the reference score values ​​corresponding to each signal strength range during the time period of 20:00-22:00 within a week.

[0059] Table 1

[0060]

[0061] For example, if the collected data are -25dBm, -30dBm, -34dBm, -44dBm, -50dBm, -68dBm, -69dBm, -70dBm, -72dBm, -81dBm, -85dBm, and -99dBm, then the statistical count X1 for the signal strength interval [-30dBm, +∞) is 2, the statistical count X2 for the signal strength interval [-67dBm, -30dBm) is 3, the statistical count X3 for the signal strength interval [-70dBm, -67dBm) is 3, the statistical count X4 for the signal strength interval [-80dBm, -70dBm) is 1, the statistical count X5 for the signal strength interval [-90dBm, -80dBm) is 2, and the statistical count X6 for the signal strength interval (-∞, -90dBm) is 1.

[0062] S103. Determine the initial network quality score of the target area based on the statistical frequency of N signal strength intervals.

[0063] In some embodiments, when the ratio of the third number of data acquisitions to the second number of data acquisitions is greater than or equal to a third preset ratio, the initial network quality score is set to a preset value. Here, the second number of data acquisitions is the number of signal strength values ​​included in the acquired data. The third number of data acquisitions is the number of signal strength values ​​among the multiple signal strength values ​​that are greater than or equal to a second threshold. Thus, when there are a large number of signal strength values ​​greater than or equal to the second threshold among the multiple signal strength values ​​acquired in the target area, setting the initial network quality score for the target area to a preset value indicates that the network quality in the target area is good. This further improves the efficiency of network quality assessment.

[0064] For example, the third number of samples is X1, which represents the number of signal strength values ​​greater than or equal to -30dBm among multiple signal strength values. The second number of samples is SUM_X = X1 + X2 + X3 + X4 + X5 + X6. The third preset ratio is 50%, and the preset value is full score. Therefore, if the ratio of the third number of samples to the second number of samples is greater than or equal to the third preset ratio, the initial network quality score is set to full score.

[0065] In some embodiments, when the ratio of the fourth number of samples to the second number of samples is less than a third preset ratio, and the ratio of the fifth number of samples to the second number of samples is greater than or equal to the third preset ratio, the initial network quality score is set to a preset score. Here, the second number of samples is the number of signal strength values ​​included in the collected data. The fourth number of samples is the number of signal strength values ​​among the multiple signal strength values ​​that are less than a third threshold and greater than a fourth threshold. The fifth number of samples is the number of signal strength values ​​among the multiple signal strength values ​​that are less than the fourth threshold.

[0066] For example, continuing to refer to Table 1, with the third threshold at -80dBm, the fourth threshold at -90dBm, the third preset ratio at 50%, and the preset score at 50, the fourth number of samples is X1+X2+X3+X4+X5, and the fifth number of samples is X1+X2+X3+X4+X5+X6. If the ratio of the fourth number of samples to the second number of samples is less than 50%, and the ratio of the fifth number of samples to the second number of samples is greater than or equal to 50%, the initial network quality score is set to 50.

[0067] In this way, when there are a large number of intervals with poor signal strength among the multiple signal strength values ​​collected in the target area, the initial network quality score for the target area can be set to a preset value to indicate that the network quality in the target area is poor. This further improves the efficiency of network quality assessment.

[0068] In some embodiments, such as Figure 3 As shown, step S102 can be implemented as follows:

[0069] S1021. Arrange the N signal intensity intervals in descending order of statistical frequency to obtain the arrangement order of the N signal intensity intervals.

[0070] For example, continuing to refer to Table 1, the statistical counts of the N signal strength intervals are arranged in descending order as X3, X2, X4, X5, X1, X6. Then the order of the N signal strength intervals is [-70dBm, -67dBm), [-67dBm, -30dBm), [-80dBm, -70dBm), [-90dBm, -80dBm), [-30dBm, +∞), (-∞, -90dBm).

[0071] S1022. Select the first M signal intensity intervals from the arrangement order.

[0072] Wherein, the ratio between the sum of the statistical counts of the first M signal strength intervals in the arrangement order and the second number of samples is greater than or equal to the second preset ratio, and the ratio between the sum of the statistical counts of the first M-1 signal strength intervals in the arrangement order and the second number of samples is less than the second preset ratio, where M is a positive integer.

[0073] The second number of samples refers to the number of signal strength values ​​included in the collected data. For example, in Table 1, the second number of samples is SUM_X = X1+X2+X3+X4+X5+X6.

[0074] For example, continuing to refer to Table 1, the statistical frequency of the N signal strength intervals is arranged in descending order as X3, X2, X4, X5, X1, X6. If Sum(X3+X2+X4) / SUM_X>= 50% and Sum(X3+X2) / SUM_X<50%, then the first M signal strength intervals are determined to be [-70dbm,-67dbm), [-67dbm,-30dbm), and [-80dbm,-70dbm].

[0075] In this way, by selecting the signal strength intervals that account for a large proportion of the total number of statistical counts to evaluate the network quality of the target area, we can improve the evaluation efficiency while ensuring the accuracy of the evaluation.

[0076] S1023. Calculate the average value of the midpoint of the first M signal intensity intervals in the sorted order.

[0077] The average of the midpoint values ​​of the first M signal strength intervals is the average of the midpoint values ​​of the first M signal strength intervals.

[0078] For example, if the first M signal strength intervals are [-70dBm, -67dBm), [-67dBm, -30dBm), and [-80dBm, -70dBm), the midpoint of the group corresponding to the signal strength interval [-70dBm, -67dBm) is -68.5dBm, the midpoint of the group corresponding to the signal strength interval [-67dBm, -30dBm) is -48.5dBm, and the midpoint of the group corresponding to the signal strength interval [-80dBm, -70dBm) is -75dBm. Therefore, the average value of the midpoints of these first M signal strength intervals is (-68.5dBm - 48.5dBm - 75dBm) / 3 = -64dBm.

[0079] S1024. Determine the initial network quality score of the target area based on the average value of the group midpoint, the upper limit and lower limit of the signal strength interval to which the average value of the group midpoint belongs.

[0080] In some embodiments, the initial network quality score of the target area satisfies the following relationship:

[0081] V = (E-Di) / (Ui-Di)*t + Ai

[0082] Where V is the initial network quality score, E is the average of the group midpoints, Di is the lower limit of the signal strength interval to which the average of the group midpoints belongs, Ui is the upper limit of the signal strength interval to which the average of the group midpoints belongs, t is the adjustment coefficient, and Ai is the reference score corresponding to the average of the group midpoints.

[0083] For example, continuing to refer to Table 1, when the first M signal strength intervals are [-70dBm, -67dBm), [-67dBm, -30dBm), and [-80dBm, -70dBm), the average value E of the group midpoint is -64dBm. Therefore, the signal strength interval to which the average value of this group midpoint belongs is [-67dBm, -30dBm), with an upper limit Ui of -67dBm and a lower limit Di of -30dBm. The reference score Ai corresponding to the average value of the group midpoint is 90. The adjustment coefficient t is 10.

[0084] The initial network quality score for the target region is V = (E-Di) / (Ui-Di)*t + Ai = (-64-(-67)) / (-30-(-67)) *10 + 90 = 90.81.

[0085] In this way, by arranging the N signal strength intervals in descending order of their statistical frequency, we obtain the order of the N signal strength intervals. Utilizing the principle of probability distribution in statistics, we determine the initial network quality score for the target area by selecting signal strength intervals with a statistical frequency exceeding a certain number. This improves evaluation efficiency while accurately assessing the network quality of the target area.

[0086] S104. If the ratio of the first number of samples to the second number of samples is greater than or equal to the first preset ratio, the initial network quality score is penalized to obtain the network quality score of the target area.

[0087] The first number of samples is the number of signal strength values ​​less than the first threshold among multiple signal strength values, and the second number of samples is the number of signal strength values ​​included in the sampled data.

[0088] For example, continuing to refer to Table 1, assume the first threshold is -80dBm and the first preset ratio is 20%. Then the first number of samples is the sum of the number of signal strength measurements corresponding to the signal strength ranges [-90dBm, -80dBm) and (-∞, -90dBm), i.e., X5 + X6. If the ratio of the first number of samples to the second number of samples is greater than or equal to the first preset ratio, i.e., (X5 + X6) / SUM_X >= 20%, a penalty is applied to the initial network quality score to obtain the network quality score for the target area.

[0089] In some embodiments, penalizing the initial network quality score is specifically implemented by deducting points from the initial network quality score.

[0090] In some embodiments, the network quality score of the target area = the initial network quality score of the target area - the deducted score.

[0091] In some embodiments, the deducted score is a preset value. For example, the preset value is 10.

[0092] For example, assuming the initial network quality score of the target area is 90.81, and the deduction score is 10, then the network quality score of the target area = 90.81 - 10 = 80.81.

[0093] In other embodiments, the deduction score is determined based on a penalty coefficient and the ratio of the first number of samples to the second number of samples.

[0094] For example, the deduction score = penalty coefficient * number of first collections / number of second collections.

[0095] For example, continuing to refer to Table 1, assuming the penalty coefficient is 50, the first number of samples is the sum of the number of signal strengths corresponding to the signal strength ranges of [-90dmb, -80dbm) and (-∞, -90dbm), i.e., X5+X6, and the ratio of the first number of samples to the second number of samples is 0.2, i.e. (X5+X6) / SUM_X = 0.2, then the deduction score is 0.2*50=10.

[0096] Therefore, without limiting the target area to a single access point (AP), determining the initial network quality score of the target area by collecting signal strength data from terminals in the target area is more realistic. If too many of the collected signal strength values ​​are below a first threshold, it indicates poor network quality in the target area. By penalizing the initial network quality score, the accuracy of the network quality assessment for the target area can be improved.

[0097] In some embodiments, if the ratio of the first number of samples to the second number of samples is less than a first preset ratio, then there is no need to penalize the initial network quality score, and the network quality score of the target area is equal to the initial network quality score.

[0098] It is understood that the above methods can be implemented by a network quality assessment device. To achieve the above functions, the network quality assessment device includes hardware structures or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, the embodiments of the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of the present invention.

[0099] In this embodiment of the invention, the network quality assessment device and the like can be divided into functional modules according to the above method examples. For example, each function can be divided into its own functional modules. The integrated modules can be implemented in hardware or as software functional modules. It should be noted that the module division in this embodiment of the invention is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0100] When dividing each function into modules according to its corresponding function. Figure 4 A possible structural diagram of the network quality assessment device involved in the above embodiments is shown. For example... Figure 4 As shown, the network quality assessment device 40 includes an acquisition module 41 and a processing module 42.

[0101] The acquisition module 41 is used to acquire collected data, which includes multiple signal strength values ​​obtained by acquiring the signal strength of terminals in the target area within a first time period.

[0102] The processing module 42 is used to determine the statistical frequency of N signal strength intervals based on the collected data; the statistical frequency of the signal strength interval is used to characterize the number of signal strength values ​​that are located in the signal strength interval among multiple signal strength values, where N is a positive integer greater than 1;

[0103] Processing module 42 is also used to determine the initial network quality score of the target area based on the statistical frequency of N signal strength intervals;

[0104] The processing module 42 is further configured to penalize the initial network quality score when the ratio of the first number of samples to the second number of samples is greater than or equal to the first preset ratio, thereby obtaining the network quality score of the target area. The first number of samples is the number of signal strength values ​​less than the first threshold among multiple signal strength values, and the second number of samples is the number of signal strength values ​​included in the sampled data.

[0105] In some embodiments, the processing module 42 is specifically used to: arrange the N signal strength intervals in descending order of statistical frequency to obtain the arrangement order of the N signal strength intervals;

[0106] Select the first M signal strength intervals from the arrangement order. The ratio between the sum of the statistical counts of the first M signal strength intervals in the arrangement order and the second number of samples is greater than or equal to the second preset ratio, and the ratio between the sum of the statistical counts of the first M-1 signal strength intervals in the arrangement order and the second number of samples is less than the second preset ratio. M is a positive integer.

[0107] Calculate the average of the midpoints of the first M signal intensity intervals in the sorted order;

[0108] The initial network quality score for the target area is determined based on the average value of the group midpoint, the upper limit and lower limit of the signal strength interval to which the average value of the group midpoint belongs.

[0109] In some embodiments, the initial network quality score of the target area satisfies the following relationship:

[0110] V = (E-Di) / (Ui-Di)*t + Ai

[0111] Where V is the initial network quality score, E is the average of the group midpoints, Di is the lower limit of the signal strength interval to which the average of the group midpoints belongs, Ui is the upper limit of the signal strength interval to which the average of the group midpoints belongs, t is the adjustment coefficient, and Ai is the reference score corresponding to the average of the group midpoints.

[0112] In some embodiments, the processing module 42 is specifically used to: set the initial network quality score to a preset value when the ratio of the third number of samples to the second number of samples is greater than or equal to a third preset ratio, wherein the third number of samples is the number of signal strength values ​​greater than or equal to a second threshold among multiple signal strength values.

[0113] In some embodiments, the first time period includes one or more target sub-time periods within the second time period, wherein the ratio of the number of terminals connected to the wireless network in the target area within the target sub-time period to the preset maximum number of terminals exceeds a fourth preset ratio.

[0114] Of course, the network quality assessment device 40 includes, but is not limited to, the unit modules listed above. Furthermore, the specific functions that the aforementioned functional units can achieve include, but are not limited to, the functions corresponding to the method steps in the above examples. For detailed descriptions of other modules of the network quality assessment device 40, please refer to the detailed descriptions of their corresponding method steps; these will not be repeated here in this embodiment of the invention.

[0115] When using integrated units, Figure 5 A possible structural diagram of the electronic device involved in the above embodiments is shown. The electronic device 500 may include a processor 501 and a memory 502. The memory 502 is used to store executable instructions of the processor 501. The processor 501 is configured to execute the instructions, causing the electronic device to perform various functions or steps in the above method embodiments.

[0116] Specifically, the processor 501 is used to control and manage the operation of the electronic device. The memory 502 is used to store the program code and data of the electronic device, such as network quality assessment methods, preset weights, preset value ranges, etc.

[0117] Furthermore, the electronic device 500 may also include a communication module. The communication module is used to support communication between the electronic device and other network entities to achieve functions such as data interaction. For example, the communication module supports communication between the electronic device and a backend server to achieve data interaction.

[0118] The processor 501 may include one or more processing cores, such as a 4-core processor or a 5-core processor. The processor 501 may include an attached processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU).

[0119] The memory 502 may include one or more computer-readable storage media, which may be non-transitory. The memory 502 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 502 is used to store at least one instruction, which is executed by the processor 501 to implement the network quality assessment method provided in the embodiments of the present invention.

[0120] This invention also provides a computer-readable storage medium including computer instructions that, when executed on the electronic device, cause the electronic device to perform the various functions or steps described in the method embodiments. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, or optical data storage device, etc.

[0121] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0122] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0123] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0124] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0125] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0126] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A network quality evaluation method characterized by comprising: The method includes: Acquire collected data, which includes multiple signal strength values ​​obtained by collecting the signal strength of terminals in the target area within a first time period; Based on the collected data, the statistical frequency of N signal strength intervals is determined; the statistical frequency of the signal strength interval is used to characterize the number of signal strength values ​​that are located in the signal strength interval among the multiple signal strength values, where N is a positive integer greater than 1; The initial network quality score for the target area is determined based on the statistical frequency of the N signal strength intervals. If the ratio of the first number of samples to the second number of samples is greater than or equal to a first preset ratio, the initial network quality score is penalized to obtain the network quality score of the target area. The first number of samples is the number of signal strength values ​​less than a first threshold among the plurality of signal strength values, and the second number of samples is the number of signal strength values ​​included in the sampled data.

2. The method of claim 1, wherein, The step of determining the initial network quality score of the target area based on the statistical frequency of the N signal strength intervals includes: The N signal intensity intervals are arranged in descending order of statistical frequency to obtain the arrangement order of the N signal intensity intervals; The first M signal strength intervals are selected from the arrangement order. The ratio between the sum of the statistical counts of the first M signal strength intervals in the arrangement order and the second number of samples is greater than or equal to the second preset ratio, and the ratio between the sum of the statistical counts of the first M-1 signal strength intervals in the arrangement order and the second number of samples is less than the second preset ratio, where M is a positive integer. Calculate the average value of the midpoint of the first M signal intensity intervals in the given arrangement order; The initial network quality score for the target area is determined based on the average value of the group midpoint, the upper limit and lower limit of the signal strength interval to which the average value of the group midpoint belongs.

3. The method according to claim 2, characterized in that, The initial network quality score for the target area satisfies the following relationship: V = (E-Di) / (Ui-Di)*t + Ai Wherein, V is the initial network quality score, E is the average value of the group midpoints, Di is the lower limit of the signal strength interval to which the average value of the group midpoints belongs, Ui is the upper limit of the signal strength interval to which the average value of the group midpoints belongs, t is the adjustment coefficient, and Ai is the reference score value corresponding to the average value of the group midpoints.

4. The method of claim 1, wherein, The step of determining the initial network quality score of the target area based on the statistical frequency of the N signal strength intervals includes: If the ratio of the third number of samples to the second number of samples is greater than or equal to a third preset ratio, the initial network quality score is set to a preset value, where the third number of samples is the number of signal strength values ​​greater than or equal to a second threshold among the plurality of signal strength values.

5. The method according to any one of claims 1 to 4, characterized in that, The first time period includes one or more target sub-time periods within the second time period, wherein the ratio of the number of terminals connected to the wireless network in the target area within the target sub-time period to the preset maximum number of terminals exceeds a fourth preset ratio.

6. A network quality assessment device, characterized in that, The device includes: The acquisition module is used to acquire collected data, which includes multiple signal strength values ​​obtained by acquiring the signal strength of terminals in the target area within a first time period. The processing module is used to determine the statistical frequency of N signal strength intervals based on the collected data; the statistical frequency of the signal strength interval is used to characterize the number of signal strength values ​​that are located in the signal strength interval among the multiple signal strength values, where N is a positive integer greater than 1; The processing module is also used to determine the initial network quality score of the target area based on the statistical frequency of the N signal strength intervals; The processing module is further configured to penalize the initial network quality score when the ratio of the first number of samples to the second number of samples is greater than or equal to a first preset ratio, thereby obtaining a network quality score for the target area. The first number of samples is the number of signal strength values ​​less than a first threshold among the plurality of signal strength values, and the second number of samples is the number of signal strength values ​​included in the sampled data.

7. The apparatus according to claim 6, characterized in that, The processing module is specifically used for: The N signal intensity intervals are arranged in descending order of statistical frequency to obtain the arrangement order of the N signal intensity intervals; The first M signal strength intervals are selected from the arrangement order. The ratio between the sum of the statistical counts of the first M signal strength intervals in the arrangement order and the second number of samples is greater than or equal to the second preset ratio, and the ratio between the sum of the statistical counts of the first M-1 signal strength intervals in the arrangement order and the second number of samples is less than the second preset ratio, where M is a positive integer. Calculate the average value of the midpoint of the first M signal intensity intervals in the given arrangement order; The initial network quality score for the target area is determined based on the average value of the group midpoint, the upper limit and lower limit of the signal strength interval to which the average value of the group midpoint belongs.

8. The apparatus of claim 7, wherein, The initial network quality score for the target area satisfies the following relationship: V = (E-Di) / (Ui-Di)*t + Ai Wherein, V is the initial network quality score, E is the average value of the group midpoints, Di is the lower limit of the signal strength interval to which the average value of the group midpoints belongs, Ui is the upper limit of the signal strength interval to which the average value of the group midpoints belongs, t is the adjustment coefficient, and Ai is the reference score value corresponding to the average value of the group midpoints.

9. The apparatus according to claim 7, characterized in that, The processing module is specifically used for: If the ratio of the third number of samples to the second number of samples is greater than or equal to a third preset ratio, the initial network quality score is set to a preset value, where the third number of samples is the number of signal strength values ​​greater than or equal to a second threshold among the plurality of signal strength values.

10. The device of any one of claims 6 to 9, wherein, The first time period includes one or more target sub-time periods within the second time period, wherein the ratio of the number of terminals connected to the wireless network in the target area within the target sub-time period to the preset maximum number of terminals exceeds a fourth preset ratio.

11. An electronic device, comprising: The electronic device includes: a processor and a memory for storing instructions executable by the processor; The processor is configured to execute the instructions, so that the electronic device performs the network quality evaluation method in any one of claims 1-5.

12. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and when the computer instructions run on the electronic device, the electronic device performs the network quality evaluation method in any one of claims 1-5.

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