A base station evaluation method, apparatus, electronic device, and storage medium

Abstract

This application discloses a base station evaluation method, apparatus, electronic device, and storage medium, relating to the field of communication technology, to address the problem that existing base station evaluation methods only consider the base station's perspective and cannot adequately meet the diverse needs of users. The method includes: acquiring access data of a target terminal device accessing a target base station at the current time; the access data includes one or more of the following: the operational status of the target base station, the network quality provided by the target base station, and the network lag level of the target terminal device; determining the target network state corresponding to the access data of the target terminal device based on a pre-established preset correspondence; the preset correspondence represents the correspondence between the access data of the sample terminal device and the target network state; and determining the user experience score of the target base station based on the target network state, the user experience score being used to evaluate the user's experience when using the target terminal device to access the target base station.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a base station evaluation method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the continuous development of communication networks, users have increasingly higher requirements for network quality. However, existing base station evaluation methods only consider the base station's indicators and performance parameters from its own perspective, which cannot adequately meet the diverse needs of users. Summary of the Invention

[0003] This application provides a base station evaluation method, apparatus, electronic device, and storage medium to address the problem that existing base station evaluation methods only consider the base station's perspective and cannot meet the diverse needs of users.

[0004] To achieve the above objectives, this application adopts the following technical solution:

[0005] In a first aspect, this application provides a base station evaluation method, comprising: acquiring access data of a target terminal device accessing a target base station at the current time; the access data includes one or more of the following: the operating status of the target base station, the network quality provided by the target base station, and the network lag level of the target terminal device; determining the target network status corresponding to the access data of the target terminal device according to a pre-established preset correspondence; the preset correspondence represents the correspondence between the access data of the sample terminal device and the target network status; and determining the difference score of the target base station according to the target network status, wherein the difference score is used to evaluate the user experience of a user accessing the target base station using the target terminal device.

[0006] Optionally, the above method further includes: acquiring access data of at least one sample terminal device that accesses different base stations at historical times; determining intermediate parameters based on the access data of one sample terminal device; the intermediate parameters include the confidence probability of each reference network state in at least one reference network state corresponding to the access data; the confidence probability represents the probability that the sample terminal device is in a reference network state; determining the reference network state with the highest confidence probability in at least one reference network state as the target network state of the sample terminal device; and establishing a preset correspondence between the access data of the sample terminal device and the target network state.

[0007] Optionally, determining intermediate parameters based on access data from a sample terminal device includes determining the confidence probability of the sample terminal device being in different reference network states based on the operating status of the target base station, the network quality provided by the target base station, and the network lag level of the sample terminal device contained in the access data.

[0008] Optionally, different reference network states correspond to different preset weights; the above-mentioned determination of the differential perception score of the target base station based on the target network state includes: obtaining the number of target terminal devices corresponding to the target network state that meets the preset conditions and the preset weights corresponding to the target network state that meets the preset conditions; the preset conditions include that when the network state of the target terminal device is the target network state, it cannot meet the network quality requirements of the network scenario in which the target terminal device is located; multiplying the number of devices by the corresponding preset weights respectively, adding the results of the multiplication, and then dividing by the total number of target terminal devices accessing the target base station to obtain the differential perception score of the target base station.

[0009] Optionally, the above method further includes: when the differential perception score of the target base station is greater than or equal to a preset score threshold, displaying a prompt message, the prompt message being used to indicate that the target base station has a network fault, and / or to indicate that the target base station needs to perform network optimization; the preset score threshold is adjusted according to the network scenario of each target terminal device accessing the target base station.

[0010] As described above, the solution in this application obtains the access data of target terminal devices accessing the target base station at the current time. Based on a pre-established correspondence, for any given terminal device, the network lag level when the user accesses the target base station using the target terminal device—i.e., user-perceived data—is used as one of the bases for predicting the target network status of the target terminal device. The target network status of the terminal device can be determined based on the pre-established correspondence and the access data. Based on the target network status of all target terminal devices accessing the target base station, a differential perception score for the target base station is obtained, which is used to evaluate the target base station. This specifically assesses the user experience of the user accessing the target base station using the terminal device. Thus, user perception is introduced into base station evaluation, solving the problem that existing base station evaluation methods only consider the base station's perspective and cannot adequately meet the diverse needs of users.

[0011] Secondly, this application provides a base station evaluation device, including: an acquisition module, a determination module, and an evaluation module;

[0012] The acquisition module is used to acquire the access data of the target terminal device that is currently accessing the target base station; the access data includes one or more of the following: the operating status of the target base station, the network quality provided by the target base station, and the network lag level of the target terminal device.

[0013] The determination module is used to determine the target network status corresponding to the access data of the target terminal device based on a pre-established preset correspondence relationship; the preset correspondence relationship represents the correspondence between the access data of the sample terminal device and the target network status.

[0014] The evaluation module is used to determine the user experience score of the target base station based on the target network status. The user experience score is used to evaluate the user's experience when accessing the target base station using the target terminal device.

[0015] The acquisition module is also used to acquire access data of at least one sample terminal device that accesses different base stations at historical times; determine intermediate parameters based on the access data of a sample terminal device; the intermediate parameters include the confidence probability of each reference network state in at least one reference network state corresponding to the access data; the confidence probability represents the probability that the sample terminal device is in a reference network state; determine the reference network state with the highest confidence probability in at least one reference network state as the target network state of the sample terminal device; and establish a preset correspondence between the access data of the sample terminal device and the target network state.

[0016] The acquisition module is also used to determine the confidence probability of the sample terminal device being in different reference network states based on the operation status of the target base station, the network quality provided by the target base station, and the network lag level of the sample terminal device contained in the access data.

[0017] Thirdly, an electronic device is provided, comprising: a memory and a processor; the memory is used to store computer-executable instructions; when the electronic device is running, the processor executes the computer-executable instructions stored in the memory to cause the electronic device to perform the base station evaluation method as described in the first aspect and any of the implementations.

[0018] Fourthly, this application provides a computer-readable storage medium, comprising: computer-executable instructions that, when executed on a computer, cause the computer to perform a base station evaluation method as described in the first aspect and any of the implementations.

[0019] For a detailed description of the second to fourth aspects and their various implementations in this application, please refer to the detailed description in the first aspect and its various implementations; and for a detailed description of the beneficial effects of the second to fourth aspects and their various implementations, please refer to the beneficial effect analysis in the first aspect and its various implementations, which will not be repeated here.

[0020] These or other aspects of this application will become more readily apparent in the following description. Attached Figure Description

[0021] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0022] Figure 1 A schematic diagram of a base station evaluation system provided in an embodiment of this application;

[0023] Figure 2 A flowchart illustrating a base station evaluation method provided in this application embodiment. Figure 1 ;

[0024] Figure 3 A flowchart illustrating a base station evaluation method provided in this application embodiment. Figure 2 ;

[0025] Figure 4 This is a schematic diagram of the internal modules of a base station evaluation device provided in an embodiment of this application;

[0026] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0028] In the description of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. The "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" means one or more, and "multiple" means two or more. The words "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences. It should be noted that in this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations.

[0029] It should be noted that any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0030] With the continuous development of communication networks, users have increasingly higher requirements for network quality. However, existing base station evaluation methods focus on assessing base station communication indicators, such as measuring channel capacity and energy consumption, and dynamically or statically testing peak cell rates, cell edge rates, terminal device access parameters, and terminal device service-related parameters. It can be seen that these base station evaluation methods only consider the base station's performance parameters and do not incorporate the user's experience of accessing the mobile network using their terminal devices, thus failing to adequately meet the diverse needs of users. Therefore, how to incorporate user perception into network optimization is one of the current research hotspots and challenges.

[0031] To address the aforementioned issues, this application provides a base station evaluation method. The method involves acquiring access data from a target terminal device accessing a target base station at the current time. This access data includes one or more of the following: the operational status of the target base station, the network quality provided by the target base station, and the network lag level of the target terminal device. Based on a pre-established correspondence, the target network state corresponding to the access data of the target terminal device is determined. The pre-established correspondence represents the relationship between the access data of the sample terminal device and the target network state. Based on the target network state, a user experience score for the target base station is determined, and this score is used to evaluate the user experience of a user accessing the target base station using the target terminal device.

[0032] As described above, in the solution of this application embodiment, by obtaining the access data of the target terminal device accessing the target base station at the current time, and based on a pre-established preset correspondence, the network lag level when the user uses the target terminal device to access the target base station, i.e., user perception data, is used as one of the bases for predicting the network status of the target terminal device. Based on the preset correspondence and the access data of the target terminal device, the target network status of the target terminal device can be determined. Based on the target network status of all target terminal devices accessing the target base station, the difference in user perception score of the target base station is obtained, and the user experience of the user using the target terminal device to access the target base station is evaluated. This introduces user perception into the base station evaluation, solving the problem that existing base station evaluation methods only consider the base station's perspective and cannot adequately meet the diverse needs of users.

[0033] The methods described in the embodiments of this application can be applied to base station evaluation systems. See also... Figure 1 As shown, the system may include a base station evaluation device 101, a target base station 102, and a terminal device 103.

[0034] The base station evaluation device 101 described in this embodiment can be a server, electronic device, computing unit, processing device, etc., used for base station evaluation. On one hand, the base station evaluation device 101 is used to acquire access data of a target terminal device accessing the target base station at the current time, and determine the target network status of the target terminal device based on a preset correspondence and the access data of the target terminal device. On the other hand, the base station evaluation device 101 determines the differential perception score of the target base station based on the target network status of the target terminal device accessing the target base station. The differential perception score is used to evaluate the user experience of a user accessing the target base station using the target terminal device.

[0035] The base station evaluation device 101, through its interface with the target base station 102, can obtain the number of target terminal devices accessing the target base station 102 and the access data of the target terminal devices at any time, thereby determining the user experience score of the target base station. The user experience score evaluates whether the base station needs network optimization from the perspective of user experience when using the target terminal devices. When the user experience score of the target base station is greater than or equal to a preset score threshold, a prompt message is displayed indicating that the target base station has a network fault.

[0036] The target base station 102 is a communication base station deployed by the operator and is a network device that supports the 3GPP TSG R15 version air interface specification. On one hand, the target base station 102 and the base station evaluation device 101 are connected via a private network for message and data transmission. On the other hand, the target base station 102 and the terminal device 103 communicate reliably via a wireless connection.

[0037] Terminal device 103 is a mobile device that can be used by users and can directly access the target base station 102 for wireless communication within the coverage area of ​​the target base station 102, and supports the 3GPP TSG R15 version air interface specification.

[0038] When implementing the base station evaluation method in this application embodiment based on the above-mentioned base station evaluation system, the target network status of the target terminal device can also be determined according to the correspondence between the access data of the target terminal device and the target network status. Furthermore, the network lag level when the user accesses the target base station using the terminal device, i.e., the user perception data, is used as one of the bases for predicting the network status of the target terminal device. The difference score of the target base station is confirmed based on the network status of all target terminal devices accessing the target base station. Thus, the user perception data is used as one of the important indicators for base station evaluation, enabling the base station to actively optimize the network based on the user perception data.

[0039] Therefore, this application incorporates user-perceived data into base station evaluation, improving the adaptability and flexibility of base stations, proactively monitoring potential problems in base stations to facilitate timely network optimization, and ensuring the stability and reliability of network performance through subsequent network optimization at the base station level, so as to provide users with better communication services.

[0040] This application provides a base station evaluation method. This method can be applied to electronic devices with computing and processing capabilities, such as base station evaluation devices, servers, and host computers. Taking the application of this method to a base station evaluation device as an example, the executing entity of this method is the base station evaluation device, see [link to relevant documentation]. Figure 2 As shown, the method includes the following steps S201-S203.

[0041] S201. Obtain the access data of the target terminal device that is currently accessing the target base station.

[0042] The access state of the target terminal device can be divided into idle state and connected state. The connected state includes pure signaling connections and connections with data transmission. A pure signaling connection occurs when the terminal device is only briefly in the connected state at a certain moment, but releases the connection without establishing a radio bearer (RB) for traffic data transmission. Examples include situations where only tracking area update (TAU) or mobile registration update (MRU) processes are performed. Since the processes related to the terminal device being in the idle state and the pure signaling connection processes are mobility management-related processes initiated by the terminal device itself, rather than manually initiated by the user, the user is completely unaware of them. This application is a base station evaluation method based on the user's perspective and aimed at meeting more user needs. Therefore, the target terminal devices accessing the target base station in this application include target terminal devices in the connected state that are performing traffic data transmission.

[0043] In some embodiments, the access data includes one or more of the following: the operational status of the target base station, the network quality provided by the target base station, and the network lag level of the target terminal device. Optionally, the access data may also include the time of access data acquisition, the location of the target terminal device, the identification identifier (ID) of the target terminal device, the location of the target base station, and the network scenario in which the target terminal device is located. The operational status of the target base station includes normal, faulty, and high load. The network quality provided by the target base station specifically includes the reference signal receiving power (RSRP) and signal-to-interference plus noise ratio (SINR) on the terminal device side. The network lag level of the target terminal device includes at least the following during the user's use of the target terminal device for internet access or voice communication: no network lag, occasional lag, and severe lag preventing internet access. The network scenario in which the target terminal device is located includes at least: parks, urban villages, transportation hubs, subways, elevators, business office areas, campuses, industrial parks, hospitals, shopping areas, smart industrial parks, VR / AR applications, and autonomous driving. A target terminal device may be located in one or more of the above scenarios at any given time.

[0044] S202. Based on the pre-established preset correspondence, determine the target network status corresponding to the access data of the target terminal device.

[0045] In some embodiments, the base station evaluation device determines a preset correspondence based on the access data corresponding to at least one sample terminal device that accesses different base stations at historical times, wherein the preset correspondence represents the correspondence between the access data of the sample terminal device and the target network status.

[0046] In some embodiments, the base station evaluation device establishes a preset correspondence between access data and target network states using the following method: The base station evaluation device acquires access data from at least one sample terminal device that has accessed different base stations at historical times. For a sample terminal device, the base station evaluation device determines intermediate parameters based on the access data of that sample terminal device. The intermediate parameters include the confidence probability of each reference network state among at least one reference network state corresponding to the access data, where the confidence probability represents the probability that the sample terminal device is in a reference network state. The base station evaluation device determines the reference network state corresponding to the highest confidence probability among the at least one reference network state as the target network state of the sample terminal device, thus establishing a preset correspondence between the access data of the sample terminal device and the target network state.

[0047] In some embodiments, the base station evaluation device determines the confidence probability of the sample terminal device being in different reference network states based on the operation status of the target base station contained in the access data, the network quality provided by the target base station, and the network lag level of the sample terminal device.

[0048] For example, based on the access data of the sample terminal device at time T1, the intermediate parameters output by the above correspondence are: reference network state 1 and its corresponding confidence probability 0.3, reference network state 2 and its corresponding confidence probability 0.6, and reference network state 3 and its corresponding confidence probability 0.1. It can be seen from the confidence probabilities corresponding to these three networks that the confidence probability corresponding to reference network state 2 is the highest. Therefore, the network state of the sample terminal device at time T1 is reference network state 2.

[0049] In some embodiments, for a target terminal device, when the base station evaluation device has acquired the access data of the target terminal device, the base station evaluation device determines the target network status of the target terminal device using a preset correspondence according to the following method:

[0050] The network status is sorted from best to worst, including at least the following five types: first-class network, second-class network, third-class network, fourth-class network, and fifth-class network.

[0051] The first preset condition includes that the target base station is operating normally, RSRP is greater than -85dBm, SINR is greater than 25dB, and the network lag level of the target terminal device is no lag.

[0052] Preset condition two includes the target base station operating normally, RSRP greater than -95dBm and less than or equal to -85dBm, SINR greater than 16dB and less than or equal to 25dB, and the target terminal device's network lag level being no lag.

[0053] Preset condition three includes the target base station operating normally, RSRP greater than -105dBm and less than or equal to -95dBm, SINR greater than 11 and less than or equal to 16, and the target terminal device experiencing no network lag.

[0054] Preset condition four includes the target base station operating normally, RSRP greater than -115dBm and less than or equal to -105dBm, SINR greater than 3 and less than or equal to 11, and the target terminal device experiencing occasional network lag.

[0055] Preset condition five includes the target base station being in a faulty or high-load condition, or the target base station being in a normal condition, RSRP being less than -115dBm, SINR being less than or equal to 3, and the target terminal device being in a severely laggy condition that prevents it from accessing the internet.

[0056] When the above-mentioned preset condition is met, the network status of the target terminal device is a first-class network.

[0057] When the above-mentioned second preset condition is met, the network status of the target terminal device is a Class II network.

[0058] When the above-mentioned preset condition three is met, the network status of the target terminal device is a Class III network.

[0059] When the above-mentioned preset condition four is met, the network status of the target terminal device is a Class IV network.

[0060] When the above-mentioned preset condition five is met, the network status of the target terminal device is a Class V network.

[0061] In some embodiments, there are enough access data samples from historical time-based sample terminal devices to include at least one access data that is the same as the access data of the target terminal device at the current time. However, the network states of the sample terminal devices corresponding to the same input data at historical time may not be the same. Therefore, based on the probability of at least one network state corresponding to the same access data at historical time, the network state corresponding to the access data of the target terminal device at the current time is predicted. The at least one network state corresponding to the same access data at historical time is used as a reference network state, and the network state with the highest probability is used as the target network state of the target terminal device.

[0062] For example, the access data of a terminal device at the current moment is as follows: the target base station is operating normally, RSRP is -100, SINR is 17, and the network lag level of the terminal device is no lag. Since the access data sample of the terminal device at the historical moment is large enough and contains the same access data, the intermediate parameters of the terminal device include two reference network states: Class 1 network and Class 2 network. The confidence probability of Class 1 network is the probability that the network state is Class 1 network in the network state sample corresponding to the same access data at the historical moment. The confidence probability of Class 2 network is the probability that the network state is Class 2 network in the network state sample corresponding to the same access data at the historical moment. Assuming that the probability of Class 1 network is 0.8 and the probability of Class 2 network is 0.2, then the target network state of the terminal device at the current moment is Class 1 network.

[0063] Optionally, the base station evaluation device can select access data and target network status corresponding to sample terminal devices of users who have complained about the operator at historical moments as a training set for a preset correspondence. Users who complain about the operator include those who, while using mobile data or voice services, have complained about the operator's network because the network quality did not meet expectations.

[0064] In some embodiments, the base station evaluation device can also determine the target network status of the target terminal device based on the device's access data, etc., according to a pre-trained prediction tree model, etc. Furthermore, in some possible application scenarios, the aforementioned preset correspondence can represent a preset tree model.

[0065] For example, the base station evaluation device can build a predictive model based on the access data of users complaining about the operator and the target network status, wherein, for each terminal device, each item of the access data of the users complaining about the operator is used as the input parameter {X1, X2, ..., X...}. n Using the target network state as the output parameter Y, a prediction tree model is built. During the model training process, multiple rounds of algorithm iterations are performed, and the optimal parameters are selected as the final parameters of the prediction tree model, thus determining the final prediction tree model. Traditional tree models can be selected, such as XGBoost, LightGBM, and CatBoost.

[0066] S203. Determine the differential perception score of the target base station based on the target network status.

[0067] In some embodiments, the base station evaluation device obtains the number of target terminal devices corresponding to a target network state that meets preset conditions and at least one preset weight corresponding to each target network state that meets preset conditions. The device multiplies the number of terminal devices by each preset weight, sums the results, and divides them by the total number of target terminal devices accessing the target base station to obtain the user experience score of the target base station. The user experience score is used to evaluate the user experience of a user accessing the target base station using the target terminal device. The preset conditions include that when the network state of the target terminal device is the target network state, the network quality requirements of the network scenario in which the target terminal device is located cannot be met.

[0068] For example, the base station evaluation device statistically analyzes the target network status of the target terminal devices output by the preset correspondence relationship, and obtains the number of target terminal devices accessing the target base station through the target base station. When the network scenario includes one or more of the following: park, urban village, transportation hub, business office area, campus, industrial park, hospital, commercial shopping area, the number of target terminal devices with target network status of fourth-class network and fifth-class network are counted respectively, and the differential perception score of the base station is calculated according to formula (1-1) and formula (1-2).

[0069]

[0070] W1 + W2 = 1 (1-2)

[0071] Where S represents the base station's differential perception score; C 总This indicates the total number of target terminal devices accessing the target base station. M1 represents a Class 5 network, M2 represents a Class 4 network, and C... M1 C M2 The numbers represent the number of target terminal devices in the target network states of Class 5 and Class 4, respectively. W1 represents the weight in state M1, and W2 represents the weight in state M2.

[0072] In some embodiments, different target network states correspond to different preset weights. Since a worse network state requires more network optimization and results in a worse user experience for terminal devices, the base station evaluation device sets the highest preset weight for Class 5 networks to uncover potential problems with the base station, while the preset weight for Class 4 networks is lower than that for Class 5 networks, and so on.

[0073] For example, the preset weight values ​​can be W1 = 0.8 and W2 = 0.2.

[0074] In a city, the coverage radius of a 4G Long Term Evolution (LTE) cell is approximately 1000 meters, and a 4G LTE base station manages at least one cell. Similarly, the coverage radius of a 5G (New Radio, NR) cell can reach several hundred meters, and a 5G NR base station manages at least one cell. Therefore, a base station has a wide coverage area, and terminal devices accessing a single base station may be located in different network scenarios, each with varying network quality requirements. Based on this, in some embodiments, the base station evaluation device adjusts preset score thresholds and preset weights corresponding to network states according to the different network quality requirements of different network scenarios.

[0075] For example, when the network scenario of the terminal device accessing the base station includes scenarios with high network quality requirements such as smart industrial parks, virtual reality (VR) applications, augmented reality (AR) applications, or autonomous driving, and the network status of the terminal device is Class III, it no longer meets the network quality requirements of the above network scenarios. Therefore, Class III network status is also included in the differential perception score formula, and the differential perception score of the base station is calculated according to formulas (2-1) and (2-2):

[0076]

[0077] W1 + W2 + W3 = 1 (2-2)

[0078] Where M3 represents a third-order network, and W3 represents the weights in the M3 state.

[0079] In some embodiments, when the differential perception score of the target base station is greater than or equal to a preset score threshold, a prompt message is displayed. The prompt message indicates that the target base station has a network fault, and / or indicates that the target base station needs network optimization. For example, the preset score threshold is 0.2.

[0080] For example, when the network scenario is a smart industrial park, or a virtual reality (VR) application, an augmented reality (AR) application, or an autonomous driving scenario, which have high requirements for network quality, the preset weight of the network status as a third-class network is increased and / or the preset score threshold is reduced when calculating the differential perception score of the base station.

[0081] For example, when the network scenario of the terminal device accessing the base station includes subways and elevators, due to the inherent reasons of these network scenarios, such as the high-speed movement of the terminal device and severe obstruction of the surrounding environment causing most radio waves to be absorbed, it is necessary to reduce the terminal device's expectation of network quality when it is in such a network scenario. When calculating the differential perception score of the base station, the base station evaluation device reduces the preset weight of the fourth-class network and / or increases the preset score threshold.

[0082] For example, W2 = 0, W1 = 1, and the differential perception score of the base station is calculated according to formula (3).

[0083]

[0084] For example, when the network scenario of the terminal device accessing the base station includes one or more of the following: park, urban village, transportation hub, business office area, campus, industrial park, hospital, commercial shopping area, smart industrial park, virtual reality (VR) application, augmented reality (AR) application, or autonomous driving, and one or more of the following: subway, elevator, the differential perception score of the base station is calculated according to formulas (2-1) and (2-2).

[0085] As can be seen from the above, in the base station evaluation method of this application embodiment, on the one hand, by acquiring the access data of terminal devices accessing the target base station at the current time, and based on a pre-established preset correspondence, the target network status of the target terminal device can be determined according to the preset correspondence and the access data of the target terminal device. Based on the target network status of all target terminal devices accessing the target base station, a differential perception score of the target base station is obtained, which is used to evaluate the target base station. The network lag level when a user accesses the target base station using the target terminal device, i.e., user perception data, is used as one of the base station's prediction criteria for the network status of the target terminal device, thus evaluating the user experience when the user accesses the target base station using the target terminal device. This introduces user perception into the base station evaluation, solving the problem that existing base station evaluation methods only consider the base station's perspective and cannot adequately meet the diverse needs of users. On the other hand, the base station evaluation device sets a preset score threshold for the differential perception score, which can be flexibly adjusted to address the different network quality requirements of different network scenarios within the target base station's coverage area.

[0086] In some implementations, see Figure 3 As shown, the method further includes the following steps S301-S303.

[0087] S301. Obtain access data of all terminal devices connected to the network in a certain region by the operator.

[0088] Due to certain needs of operators, such as statistical network key performance indicators (KPIs), it is necessary to conduct an overall assessment of the base station network deployment in a certain city or region. The base station assessment device acquires access data of all terminal devices accessing the entire network at multiple times, with each base station as the unit. Here, "the entire network" refers to the scope of all base station networks deployed by the operator in that city or region.

[0089] In some embodiments, the base station evaluation device can obtain access data of all terminal devices accessing the entire network at typical times in the city or region, such as 9:00 AM, 3:00 PM, and 9:00 PM on weekdays.

[0090] S302. For each base station in the region, calculate the differential perception score based on the access data of all connected terminal devices and the preset correspondence.

[0091] For specific steps, please refer to S201-S203.

[0092] Optionally, access data of all terminal devices in the entire network during the process of using mobile data or voice at a certain moment can be collected. Based on the aforementioned prediction tree model and the access data of all terminal devices in the network, for each terminal device, the access data of the terminal device is input into the model to predict its target network status, and then the latest network status of terminal devices in the entire network can be predicted.

[0093] S303. Calculate the difference score of the base station network deployed by the operator in the region.

[0094] Multiply the differential perception score of each base station by the proportion of the total number of terminal devices accessing it at the current time to the total number of terminal devices accessing the entire network in the city or region, and add the results together to obtain the differential perception score of the base station network deployed by the operator in the city or region, i.e. the differential perception score of the entire network. Calculate the differential perception score of the entire network according to formula (4).

[0095] S = S1 × P1 + S2 × P2 + ... + S n ×P n (4)

[0096] Where S is the overall negative perception score across the entire network, S n For the differential perception score of the nth base station, P n This represents the proportion of the total number of terminal devices accessing the nth base station to the total number of terminal devices accessing the entire network.

[0097] As can be seen from the above, in the method described in this application embodiment, the base station evaluation device calculates the difference score of any base station of the operator in a certain city or region, taking the base station as the unit. Then, the difference score of each base station is multiplied by the proportion of the total number of terminal devices accessing that base station to the total number of terminal devices accessing the entire network, thereby obtaining the overall difference score of the operator in that city or region. Based on the overall difference score, the operator can be assisted in analyzing network deployment, big data KPI analysis, user satisfaction analysis, etc.

[0098] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of this application 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 this application.

[0099] This application embodiment can divide the base station evaluation device into functional modules according to the above method example. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0100] This application also provides a schematic diagram of the internal modules of a base station evaluation device, such as... Figure 4 As shown, the device includes an acquisition module 401, a determination module 402, and an evaluation module 403.

[0101] The acquisition module is used to acquire the access data of the target terminal device that is currently accessing the target base station.

[0102] In some embodiments, the access data includes one or more of the following: the operating status of the target base station, the network quality provided by the target base station, and the network lag level of the terminal device.

[0103] The acquisition module is further configured to acquire access data of at least one sample terminal device that has accessed different base stations at historical times; determine intermediate parameters based on the access data of a sample terminal device; the intermediate parameters include the confidence probability of each reference network state in at least one reference network state corresponding to the access data; the confidence probability represents the probability that the sample terminal device is in a reference network state; determine the reference network state with the highest confidence probability in at least one reference network state as the target network state of the sample terminal device; and establish a preset correspondence between the access data of the sample terminal device and the target network state.

[0104] The acquisition module is also used to determine the confidence probability of the sample terminal device being in different reference network states based on the operation status of the target base station, the network quality provided by the target base station, and the network lag level of the sample terminal device contained in the access data.

[0105] The determination module is used to determine the target network status corresponding to the access data of the target terminal device based on the pre-established preset correspondence relationship; the preset correspondence relationship represents the correspondence between the access data of the sample terminal device and the target network status.

[0106] The evaluation module is used to determine the user experience score of the target base station based on the target network status. The user experience score is used to evaluate the user's experience when accessing the target base station using the target terminal device.

[0107] The evaluation module is also used to obtain the number of target terminal devices corresponding to the target network state that meets the preset conditions and the preset weights corresponding to the target network state that meets the preset conditions. The preset conditions include that when the network state of the target terminal device is the target network state, the network quality requirements of the network scenario in which the target terminal device is located cannot be met. The number of devices is multiplied by the corresponding preset weights, the results of the multiplication are added together, and then divided by the total number of target terminal devices connected to the target base station to obtain the differential perception score of the target base station.

[0108] The evaluation module is also used to display a prompt message when the differential perception score of the target base station is greater than or equal to a preset score threshold. The prompt message is used to indicate that the target base station has a network fault and / or to indicate that the target base station needs to perform network optimization. The preset score threshold is adjusted according to the network scenario of each target terminal device accessing the target base station.

[0109] When implementing the communication method in this application embodiment, on the one hand, a correspondence is established between the access data of a terminal device and the network status of the terminal device. The network lag level when a user accesses a target base station using a terminal device (i.e., user-perceived data) is used as one of the important indicators for network optimization of the target base station. This yields the network status of the terminal device accessing the target base station. Based on the network status, the base station's differential perception score is calculated to determine if the base station has a fault, thus enabling proactive network optimization on the base station side. This application incorporates user-perceived data into base station evaluation, improving network adaptability and flexibility, proactively monitoring potential network problems for timely network optimization, and focusing more on user perception while ensuring network performance stability and reliability, thereby improving user experience. On the other hand, according to the calculation method for the network-wide differential perception score in this application, the differential perception scores of all base stations deployed by an operator in a certain city or region are multiplied by the proportion of the number of terminal devices currently accessing that base station to the total number of terminal devices accessing all base stations in that region. This yields the differential perception score of the base station network deployed by the operator in that city or region. Therefore, by taking base stations as the unit, calculating the user satisfaction score of any base station of a certain operator in a certain city or region, and obtaining the proportion of the number of access terminal devices of each base station to the total number of access terminal devices in the entire network, the user satisfaction score of the base station network deployed by the operator in that city or region can be obtained. Based on the user satisfaction score of the entire network, operators can be assisted in analyzing network deployment, big data KPI analysis, user satisfaction analysis, etc.

[0110] Figure 5 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application, such as... Figure 5As shown, the electronic device includes a processor 501 and a bus 504. Optionally, the electronic device may also include a memory 502; alternatively, the electronic device may also include a communication interface 503. The processor 501 may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor 501 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor 501 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc. The communication interface 503 is used to connect with other devices through a communication network. The communication network may be Ethernet, a private network, a wireless access network, a wireless local area network (WLAN), etc. The memory 502 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. As one possible implementation, the memory 502 may exist independently of the processor 501. The memory 502 may be connected to the processor 501 via a bus 504 for storing instructions or program code. When the processor 501 calls and executes the instructions or program code stored in the memory 502, it can implement the communication method provided in this application embodiment. In another possible implementation, the memory 502 may also be integrated with the processor 501. The bus 504 may be an extended industry standard architecture (EISA) bus, etc. The 504 bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0111] Some embodiments of this application provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing computer program instructions that, when executed on a computer, cause the computer to perform the method as described in any of the above embodiments.

[0112] For example, the aforementioned computer-readable storage media may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes), optical discs (e.g., compact disks (23CDs), digital versatile disks (DVDs), etc.), smart cards and flash memory devices (e.g., erasable programmable read-only memory, EPROM), cards, sticks, or key drives, etc.). The various computer-readable storage media disclosed in this application may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0113] This application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the method of any of the above embodiments.

[0114] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A base station evaluation method, characterized by, The method comprises: obtaining access data of a target terminal device accessing a target base station at a current time point; the access data comprises running conditions of the target base station, network quality provided by the target base station, and network jamming degree of the target terminal device; determining a target network state corresponding to the access data of the target terminal device according to a preset correspondence relationship; the preset correspondence relationship represents a correspondence relationship between access data of a sample terminal device and the target network state; determining a difference sensitivity score of the target base station according to the target network state; the difference sensitivity score is used to evaluate user experience of a user using the target terminal device to access the target base station; obtaining access data of at least one sample terminal device accessing different base stations at a historical time point; wherein the access data of the sample terminal device is complaint data of the sample terminal device; determining an intermediate parameter according to the access data of one sample terminal device; the intermediate parameter comprises a confidence probability of each reference network state corresponding to the access data, in at least one reference network state; the confidence probability represents a possibility that the sample terminal device is in the reference network state; determining a reference network state with the highest confidence probability in the at least one reference network state as a target network state of the sample terminal device; establishing a preset correspondence relationship between the access data of the sample terminal device and the target network state; different reference network states correspond to different preset weights; the determining of the difference sensitivity score of the target base station according to the target network state comprises: obtaining a device quantity of the target terminal device corresponding to the target network state satisfying a preset condition and a preset weight corresponding to the target network state satisfying the preset condition; the preset condition comprises that when the network state of the target terminal device is the target network state, the requirement of the network scenario in which the target terminal device is located on network quality cannot be met; multiplying the device quantity by the corresponding preset weight respectively, adding the results obtained after multiplication, and then dividing by the total number of the target terminal devices accessing the target base station to obtain the difference sensitivity score of the target base station.

2. The method of claim 1, wherein, The determining of the intermediate parameter according to the access data of the one sample terminal device comprises: determining the confidence probability of the sample terminal device in different reference network states according to the running conditions of the target base station, the network quality provided by the target base station, and the network jamming degree of the sample terminal device contained in the access data.

3. The method of claim 1, wherein, The method further comprises: when the difference sensitivity score of the target base station is greater than or equal to a preset score threshold, displaying prompt information; the prompt information is used to indicate that the target base station has a network fault, and / or, to indicate that the target base station needs to be optimized; the preset score threshold is adjusted according to a network scenario in which each target terminal device accessing the target base station is located.

4. A base station evaluation device, characterized in that, The device comprises: an obtaining module, configured to obtain access data of a target terminal device accessing a target base station at a current time point; The access data comprises one or more of the following: running condition of the target base station, network quality provided by the target base station, and network jamming degree of the target terminal device; The determining module is configured to determine, according to a preset correspondence, a target network state corresponding to the access data of the target terminal device; The preset correspondence represents a correspondence between the access data of a sample terminal device and the target network state; The evaluation module is configured to: acquire a device quantity of the target terminal device corresponding to the target network state satisfying a preset condition and a preset weight corresponding to the target network state satisfying the preset condition; The preset condition comprises that, when the network state of the target terminal device is the target network state, the network quality requirement of the network scene in which the target terminal device is located cannot be met; The device quantity is multiplied by the corresponding preset weight, the obtained results are added, and then divided by a total number of the target terminal devices accessing the target base station, to obtain a difference sensitivity score of the target base station, which is used to evaluate user experience of users using the target terminal device to access the target base station. The acquisition module is further configured to acquire access data of at least one sample terminal device accessing different base stations at a historical moment; wherein the access data of the sample terminal device is complaint data of the sample terminal device; determine an intermediate parameter according to the access data of one sample terminal device; the intermediate parameter comprises a confidence probability of each reference network state corresponding to the access data in at least one reference network state; the confidence probability represents a possibility that the sample terminal device is in the reference network state; determine, as a target network state of the sample terminal device, a reference network state with the highest confidence probability in the at least one reference network state; and establish a preset correspondence between the access data of the sample terminal device and the target network state. The evaluation module is specifically configured to: acquire a device quantity of the target terminal device corresponding to the target network state satisfying a preset condition and a preset weight corresponding to the target network state satisfying the preset condition; and the preset condition comprises that, when the network state of the target terminal device is the target network state, the network quality requirement of the network scene in which the target terminal device is located cannot be met. The device quantity is multiplied by the corresponding preset weight, the obtained results are added, and then divided by a total number of the target terminal devices accessing the target base station, to obtain a difference sensitivity score of the target base station.

5. The apparatus of claim 4, wherein: The acquisition module is further configured to determine the confidence probability of the sample terminal device in different reference network states according to the running condition of the target base station, the network quality provided by the target base station, and the network jamming degree of the sample terminal device contained in the access data.

6. An electronic device, comprising: The electronic device comprises a memory and a processor; the memory is used to store computer execution instructions; when the electronic device is running, the processor executes the computer execution instructions stored in the memory, so that the electronic device executes the base station evaluation method according to any one of claims 1-3.

7. A computer-readable storage medium, characterized in that, The computer program is stored in the computer readable storage medium, and the computer program is executed by the processor to implement the base station evaluation method according to any one of claims 1-3.

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