Network Quality Prediction Method, Device, Electronic Device, Storage Medium, and Product

Abstract

The present application relates to a network quality prediction method, apparatus, electronic device, storage medium, and product. The method includes: if a network quality prediction start condition is satisfied, acquiring radio frequency fingerprint information of a communication network connected to the electronic device within a preset time period; determining a movement trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of the communication network; predicting the quality of the network to be connected by the electronic device within a prediction time period according to the movement trajectory and a preset network quality map, and generating a prediction result; wherein the preset network quality map is used to represent the correspondence between a preset communication network accessed by the electronic device on a movement route and the network quality of the preset communication network. Therefore, the accuracy of network quality prediction is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and particularly to a network quality prediction method, apparatus, electronic device, storage medium, and product. Background Art

[0002] With the rapid development of Internet technology, a variety of application programs have emerged, enriching people's work and life. However, when users use application programs during travel, since multiple base stations are involved in providing network services for the application programs during travel, and the network quality of the multiple base stations varies, therefore, during users' travel, a stable network service cannot be provided for the application programs being used by the users.

[0003] Therefore, during users' travel, it is necessary to use a network quality prediction method to predict the network quality, so as to adjust the networking strategy in real time based on the prediction result to meet the network requirements of the application programs being used by the users. However, the accuracy of the prediction results obtained by traditional network quality prediction methods is relatively low. Summary of the Invention

[0004] Embodiments of the present application provide a network quality prediction method, apparatus, electronic device, storage medium, and product, which can improve the accuracy of network quality prediction.

[0005] On the one hand, a network quality prediction method is provided, which is applied to an electronic device. The method includes:

[0006] If a network quality prediction start condition is satisfied, obtain the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period;

[0007] Determine the movement trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of each communication network;

[0008] Perform quality prediction on the network to be connected by the electronic device during a prediction time period according to the movement trajectory and a preset network quality map, and generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the movement route and the network quality of the preset communication networks.

[0009] On the other hand, a network quality prediction apparatus is provided, which is applied to an electronic device. The apparatus includes:

[0010] A radio frequency fingerprint information acquisition module, configured to obtain the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period if a network quality prediction start condition is satisfied;

[0011] The motion trajectory determination module is configured to determine the motion trajectory of the electronic device within the preset time period according to the RF fingerprint information of each of the communication networks;

[0012] The network quality prediction module is configured to predict the quality of the network to be connected by the electronic device within the prediction time period according to the motion trajectory and the preset network quality map, and generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the moving route and the network quality of the preset communication networks.

[0013] On the other hand, an electronic device is provided, including a memory and a processor. A computer program is stored in the memory. When the computer program is executed by the processor, the processor executes the steps of the network quality prediction method as described above.

[0014] On the other hand, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the network quality prediction method as described above are implemented.

[0015] On the other hand, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps of the network quality prediction method as described above are implemented.

[0016] For the above network quality prediction method, device, electronic device, storage medium, and product, if the network quality prediction start condition is satisfied, the RF fingerprint information of the communication network connected to the electronic device within the preset time period is obtained; according to the RF fingerprint information of the communication network, the motion trajectory of the electronic device within the preset time period is determined; according to the motion trajectory and the preset network quality map, the quality of the network to be connected by the electronic device within the prediction time period is predicted, and a prediction result is generated; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the moving route and the network quality of the preset communication networks.

[0017] Obtain the radio frequency fingerprint information of the communication network connected to the electronic device within a preset time period. Since the current location of the electronic device can be identified by recognizing the radio frequency fingerprint information of the communication network, the movement trajectory of the electronic device within the preset time period can be determined according to the radio frequency fingerprint information of each communication network connected to the electronic device within the preset time period. On the one hand, it is not necessary to determine the movement trajectory of the electronic device through GPS, so it can be applied to scenarios where GPS signals cannot be obtained or cannot be accurately obtained. On the other hand, since the preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device on the moving route and the network quality of the preset communication network. Therefore, based on the current location of the electronic device on the moving route, the predicted trajectory of the electronic device within the prediction time period is further determined, and then the preset communication network corresponding to the predicted trajectory and the network quality of the preset communication network can be accurately determined from the preset network quality map. Finally, the quality prediction of the network to be connected by the electronic device within the prediction time period is realized. Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 It is an application environment diagram of the network quality prediction method in an embodiment;

[0020] Figure 2 It is a flowchart of the network quality prediction method in an embodiment;

[0021] Figure 3 For Figure 2 It is a flowchart of the method for determining the movement trajectory of the electronic device within a preset time period in

[0022] Figure 4 It is a schematic diagram of characteristic positions in the subway scenario in an embodiment;

[0023] Figure 5 It is a schematic diagram of the preset radio frequency fingerprint map in an embodiment;

[0024] Figure 6 For Figure 3 It is a flowchart of the method for generating the movement trajectory of the electronic device within a preset time period based on the characteristic positions corresponding to each preset communication network in

[0025] Figure 7 It is a schematic diagram of the preset position sequence in an embodiment;

[0026] Figure 8 For Figure 2 The flowchart of the method for predicting the quality of the network to be connected by the electronic device within the prediction time period according to the motion trajectory and the preset network quality map, and generating a prediction result;

[0027] Figure 9 For Figure 8 The flowchart of the method for predicting the quality of the network to be connected by the electronic device within the prediction time period when the motion state of the electronic device is a stationary state;

[0028] Figure 10 For Figure 9 The flowchart of the method for predicting the quality of the network to be connected by the electronic device within the prediction time period according to the target feature position in the motion trajectory, combining the preset radio frequency fingerprint map and the first preset network quality map;

[0029] Figure 11 The flowchart of the method for predicting the quality of the network to be connected by the electronic device within the prediction time period when the motion state of the electronic device is a moving state;

[0030] Figure 12 For Figure 11 The flowchart of the method for predicting the quality of the network to be connected by the electronic device within the prediction time period based on the current feature position and at least one predicted feature position, combining the preset radio frequency fingerprint map and the first preset network quality map, and generating a second prediction result;

[0031] Figure 13 The schematic diagram of the network quality prediction method in another embodiment;

[0032] Figure 14 The schematic diagram of the network quality prediction method in a specific embodiment;

[0033] Figure 15 The structural block diagram of the network quality prediction device in an embodiment;

[0034] Figure 16 For Figure 15 The structural block diagram of the motion trajectory determination module in;

[0035] Figure 17 The internal structural schematic diagram of the electronic device in an embodiment. Detailed implementation manners

[0036] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0037] It can be understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of this application, the first prediction result may be referred to as the second prediction result, and similarly, the second prediction result may be referred to as the first prediction result. Both the first prediction result and the second prediction result are prediction results, but they are not the same prediction result.

[0038] When a user uses an application during a trip, since the user is in a moving state during the trip, multiple base stations are involved in providing network services for the application, and the network quality of multiple base stations varies. Therefore, during the user's trip, a stable network service cannot be provided for the application that the user is using.

[0039] To meet the network requirements of the application that the user is using, during the user's trip, a method for predicting network quality needs to be adopted to predict the network quality and adjust the networking strategy in real time based on the prediction result. Most traditional network quality prediction methods obtain the user's current location and movement information through GPS, and then predict the future network quality of the electronic device based on the user's current location and movement information. Traditional network quality prediction methods need to obtain the user's current location and movement information through GPS. On the one hand, turning on the GPS function will greatly increase the power consumption of the terminal; on the other hand, in underground sections (such as scenarios of taking the subway, being in an underground tunnel, or being in an underground parking lot), indoors (such as a large shopping mall), or areas with severe shielding in the urban area (scenarios with high-rise buildings), the situation of being unable to obtain the GPS signal or being unable to accurately obtain the GPS signal often occurs. Furthermore, network quality prediction cannot be performed based on the GPS signal, or the accuracy of the prediction result obtained by predicting the network quality based on the GPS signal is relatively low.

[0040] To solve the problem that the accuracy of the prediction result obtained by predicting the network quality of an electronic device using traditional network quality prediction methods is relatively low. This application proposes a new network quality prediction method. Figure 1 It is a schematic diagram of the application environment of the network quality prediction method in an embodiment. As Figure 1As shown in the figure, the application environment includes an electronic device 120 and multiple base stations 140. The electronic device 120 can establish a communication connection with the base stations 140. If the network quality prediction activation condition is met, the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period is obtained; according to the radio frequency fingerprint information of each communication network, the movement trajectory of the electronic device within the preset time period is determined; according to the movement trajectory and the preset network quality map, the network quality of the network to be connected by the electronic device during the prediction time period is predicted to generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks on the movement route of the electronic device and the network quality of the preset communication networks. Among them, the electronic device 120 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc.

[0041] Figure 2 It is a flowchart of a network quality prediction method in an embodiment. The network quality prediction method in this embodiment is described by taking it as running on Figure 1 the electronic device as an example. As Figure 2 shown in the figure, the network quality prediction method includes steps 220 to 260, where

[0042] Step 220, if the network quality prediction activation condition is met, the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period is obtained.

[0043] Among them, the network quality prediction activation condition is used to represent the condition for the electronic device to activate network quality prediction. The electronic device can automatically activate network quality prediction when the network quality prediction activation condition is met; of course, the electronic device can also receive a user operation to activate network quality prediction when the network quality prediction activation condition is met, and this application does not make any limitations in this regard. Here, the network quality prediction activation condition can include conditions related to the network quality status, the operating status of the electronic device, etc. For example, the network quality prediction activation condition can be that the network quality of the communication network currently connected to the electronic device is lower than a preset network quality threshold. Among them, the operating status of the electronic device includes the operating status of the CPU of the electronic device, the operating status of application programs, the operating status of the battery, etc., and this application does not make any limitations in this regard. For example, the network quality prediction activation condition can be that the current load of the CPU of the electronic device exceeds a first preset load threshold, or is less than a second preset load threshold, etc.; the network quality prediction activation condition can also be that the current remaining power of the electronic device is lower than a preset power threshold; it can also be that the application program currently running on the electronic device is a preset application program, etc. Of course, the network quality prediction activation condition can also be a combination of any one or more of the above conditions, and this application does not make any limitations in this regard.

[0044] Here, the communication network refers to the network provided by the base station, generally referring to the serving cell. The serving cell, also known as a cellular cell, refers to the area covered by a base station or a part of the base station (sector antenna) in a cellular mobile communication system. Within this area, the electronic device can communicate with the base station through a wireless channel. Generally speaking, one base station is one serving cell. Therefore, the RF fingerprint information of the communication network refers to the RF fingerprint information of the serving cell. Among them, the RF fingerprint information refers to the attribute information of the signals transmitted by different serving cells received by the electronic device at the current location. By identifying the RF fingerprint information of the communication network, the current location of the electronic device can be identified.

[0045] When predicting the quality of the network to which the electronic device is to be connected during the user's travel, first, it is determined whether the electronic device meets the network quality prediction start condition. Specifically, it can be determined whether the network quality of the communication network currently connected to the electronic device is lower than a preset network quality threshold. If so, the network quality prediction process is started; if not, the network quality prediction process is not started.

[0046] After starting the network quality prediction process, the RF fingerprint information of each communication network connected to the electronic device within a preset time period is obtained in sequence. That is, in chronological order, the RF fingerprint information of each historical communication network connected to the electronic device within a preset time period is obtained. The preset time period here can be a time period between the current time point and any historical time point. For example, the preset time period can be a time period between the current time point (8:00 AM) and the historical time point (7:55 AM). Of course, this application does not make any limitations in this regard. For example, the RF fingerprint information 1... RF fingerprint information n of different communication networks connected to the electronic device within the preset time period (such as 7:55 AM - 8:00 AM) is obtained in sequence. Here, n can take any natural number greater than or equal to 1.

[0047] Step 240, determine the movement trajectory of the electronic device within the preset time period according to the RF fingerprint information of each communication network.

[0048] After obtaining the RF fingerprint information of each communication network connected to the electronic device within the preset time period, since the current location of the electronic device can be identified by identifying the RF fingerprint information of the communication network, the movement trajectory of the electronic device within the preset time period can be determined according to the RF fingerprint information of each communication network.

[0049] Specifically, the RF fingerprint information of each communication network connected to the electronic device within the preset time period is identified in sequence to obtain the current location of the electronic device corresponding to each communication network. Based on the multiple current locations of the electronic device within the preset time period, the movement trajectory of the electronic device within the preset time period is generated.

[0050] Step 260: According to the movement trajectory and the preset network quality map, perform quality prediction on the network to be connected by the electronic device during the prediction time period, and generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the movement route and the network quality of the preset communication networks.

[0051] Among them, the preset network quality map is generated based on the preset communication networks accessed by the user when using the electronic device on the movement route and the network quality of the preset communication networks. The preset network quality map can be established based on the historical data of the preset communication networks accessed by different users when using the electronic device on the movement route and the network quality of the preset communication networks. That is, when predicting the network quality of a certain user when using the electronic device on the movement route, the prediction is based on the corresponding preset network quality map of the user when using the electronic device on the movement route. It can realize targeted prediction of the network quality of different users when using the electronic device on the movement route, and meet the diverse Internet access needs of different users. The preset communication network here refers to the serving cell accessed when using the preset application program, and the network quality of the preset communication network can be represented by the network quality level and network quality parameters. For example, the movement route here can be the user's commuting route to work. Specifically, if on the user's commuting route to work, the electronic device accesses a certain preset communication network at different characteristic positions and obtains the network quality of the preset communication network.

[0052] Then, after generating the movement trajectory of the electronic device within the preset time period, according to the movement trajectory and the preset network quality map, perform quality prediction on the network to be connected by the electronic device during the prediction time period, and generate a prediction result. According to the movement trajectory of the electronic device within the preset time period, the current position of the electronic device on the movement route can be determined, and then the predicted trajectory of the electronic device during the prediction time period can be determined. And since the preset network quality map records the corresponding relationship between the preset communication networks accessed by the electronic device on the movement route and the network quality of the preset communication networks. Therefore, based on the predicted trajectory, the preset communication network corresponding to the predicted trajectory and the network quality of the preset communication network can be obtained from the preset network quality map, that is, the network quality of the preset communication network and the preset communication network during the prediction time period is obtained. At this time, the quality prediction of the network to be connected by the electronic device during the prediction time period is realized, and a prediction result is generated.

[0053] In the embodiments of the present application, radio frequency fingerprint information of a communication network connected to an electronic device within a preset time period is obtained. Since the current location of the electronic device can be identified by recognizing the radio frequency fingerprint information of the communication network, the movement trajectory of the electronic device within the preset time period can be determined according to the radio frequency fingerprint information of each communication network connected to the electronic device within the preset time period. On the one hand, it is not necessary to determine the movement trajectory of the electronic device through GPS, so it can be applied to scenarios where GPS signals cannot be obtained or cannot be accurately obtained. On the other hand, since the preset network quality map is used to represent the correspondence between the preset communication networks accessed by the electronic device on the moving route and the network quality of the preset communication networks. Therefore, based on the current location of the electronic device on the moving route, the predicted trajectory of the electronic device within the prediction time period is further determined, and then the preset communication network corresponding to the predicted trajectory and the network quality of the preset communication network can be accurately determined from the preset network quality map. Finally, the quality prediction of the network to be connected by the electronic device within the prediction time period is realized.

[0054] In the previous embodiment, a network quality prediction method was described. In this embodiment, step 240 is further described. Determining the movement trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of each communication network includes:

[0055] Sequentially matching the radio frequency fingerprint information of each communication network with a preset radio frequency fingerprint map to determine the movement trajectory of the electronic device within the preset time period; the preset radio frequency fingerprint map is used to represent the radio frequency fingerprint information of the preset communication networks corresponding to each characteristic position on the moving route of the electronic device.

[0056] Among them, the radio frequency fingerprint information of the preset communication networks accessed by the electronic device at each characteristic position on the moving route is recorded in the preset radio frequency fingerprint map. Here, the preset radio frequency fingerprint map can be stored in the database in the form of a data table. Suppose that on the user's commuting route to work (such as from subway station A - subway station B - subway station C), that is, the moving route of the electronic device is the same as the commuting route to work at this time. At this time, a partial data table corresponding to the preset radio frequency fingerprint map is shown in Table 1-1 below:

[0057] Table 1-1

[0058]

[0059]

[0060] Here, the serving cell can be abbreviated as the cell. Among them, the cell identifier, the minimum signal strength of the cell, and the maximum signal strength of the cell are all radio frequency fingerprint information of the communication network.

[0061] Therefore, the RF fingerprint information of each communication network connected to the electronic device within a preset time period can be sequentially matched with a preset RF fingerprint map to determine the movement trajectory of the electronic device within the preset time period. Specifically, by identifying the RF fingerprint information of each communication network, the current position of the electronic device can be identified. Connecting the current positions corresponding to each communication network in sequence yields the movement trajectory of the electronic device within the preset time period.

[0062] In the embodiments of the present application, the preset RF fingerprint map is used to represent the RF fingerprint information of the preset communication network corresponding to each feature position on the movement route of the electronic device. Therefore, when determining the movement trajectory of the electronic device within a preset time period based on the RF fingerprint information of each communication network, the movement trajectory of the electronic device within the preset time period can be directly determined by sequentially matching the RF fingerprint information of each communication network with the preset RF fingerprint map. It is not necessary to determine the movement trajectory of the electronic device through GPS. Therefore, it can be applied to scenarios where GPS signals cannot be obtained or cannot be accurately obtained.

[0063] In one embodiment, the RF fingerprint information includes cell identification and signal strength information. Here, as Figure 3 shown, the steps of sequentially matching the RF fingerprint information of each communication network with the preset RF fingerprint map to determine the movement trajectory of the electronic device within a preset time period are further described in detail, including:

[0064] Step 320, for each communication network, obtain the cell identification and signal strength information of the communication network from the RF fingerprint information of the communication network.

[0065] Among them, the RF fingerprint information includes cell identification and signal strength information. By identifying the RF fingerprint information of the communication network, the current position of the electronic device can be identified. It is known that the cell identifications accessed at different feature positions on the movement route of the electronic device are different, and the signal strength information corresponding to the cell is also different. Therefore, by identifying the cell identification and signal strength information of the communication network, the current position of the electronic device can be accurately identified.

[0066] Therefore, after obtaining the RF fingerprint information of each communication network connected to the electronic device within a preset time period, for each communication network, obtain the cell identification and signal strength information of the communication network from the RF fingerprint information of the communication network. So as to subsequently determine the current position of the electronic device on the movement route based on the cell identification and signal strength information of the communication network.

[0067] Step 340, match the cell identification and signal strength information of the communication network with the cell identification and signal strength information of the preset communication network in the preset RF fingerprint map to determine the preset communication network matched with each communication network.

[0068] Assume in the scenario of taking the subway, as Figure 4 shown, the positions at both ends of the subway platform are respectively defined as feature positions, and each feature position represents a position area, including the boarding areas in two advancing directions of the subway train and the middle area between the two boarding areas. Taking Feature Position 1 (Point of Interest 1) as an example, Feature Position 1 includes the boarding area of the last car at the rear of the train in the advancing direction 1, the boarding area of the first car at the front of the train in the advancing direction 2, and the middle area between the two boarding areas. Similarly, the corresponding areas of Feature Position 2 (Point of Interest 2) and Feature Position 3 (Point of Interest 3) can be obtained.

[0069] Combined with Figure 5 shown, it is a schematic diagram of a preset RF fingerprint map in an embodiment. Assume in the scenario of taking the subway, the subway has 2 running directions (train advancing direction 1 and train advancing direction 2) between the feature positions (such as Endpoint 1 of Station A, Middle of Platform A, Endpoint 2 of Station A, Between Stations A and B, Endpoint 1 of Station B). The preset communication network corresponding to Endpoint 1 of Station A includes Cell 1 (cell1), Cell 2 (cell2), Cell 3 (cell3), and Cell 4 (cell4); the preset communication network corresponding to the middle of Platform A includes Cell 13 (cell13), Cell 14 (cell14), Cell 15 (cell15), Cell 16 (cell16), and Cell 1 (cell1); the preset communication network corresponding to Endpoint 2 of Station A includes Cell 5 (cell5), Cell 6 (cell6), Cell 7 (cell7), Cell 8 (cell8), and Cell 11 (cell11); the preset communication network corresponding to between Stations A and B includes Cell 17 (cell17), Cell 18 (cell18), Cell 19 (cell19), Cell 20 (cell20), and Cell 1 (cell1); the preset communication network corresponding to Endpoint 1 of Station B includes Cell 9 (cell9), Cell 10 (cell10), Cell 11 (cell11), Cell 12 (cell12), and Cell 1 (cell1).

[0070] First, match the cell identifiers of the communication network with the cell identifiers of the preset communication network in the preset RF fingerprint map; second, match the signal strength information of the communication network with the signal strength information corresponding to the mutually matched cell identifiers in the preset RF fingerprint map. Finally, take the preset communication network with both the cell identifier and the signal strength information matched as the preset communication network matched with this communication network.

[0071] For each communication network, a preset communication network matching the communication network is determined. For example, the cell identifier of the first communication network connected to the electronic device within a preset time period is obtained as: 1, and its signal strength information is: -110 to -100. Then, in combination with Table 1-1, the cell identifier and signal strength information of the first communication network are matched with the cell identifier and signal strength information of the preset communication network in the preset radio frequency fingerprint map, and the preset communication network matching the first communication network is determined to be the communication network corresponding to A station endpoint 1. Of course, there may also be multiple preset communication networks determined to match the first communication network, and here, no limitation is made in this regard. Similarly, the preset communication networks matching each communication network are determined in turn. Of course, there may also be multiple preset communication networks determined to match each communication network, and here, no limitation is made in this regard.

[0072] Step 360, generate the movement trajectory of the electronic device within the preset time period based on the characteristic positions corresponding to each preset communication network.

[0073] After the preset communication networks matching each communication network are determined in turn, if the number of preset communication networks corresponding to each communication network is multiple, then for each communication network, first determine the target preset communication network from the multiple preset communication networks. Obtain the characteristic positions corresponding to each target preset communication network, and generate the movement trajectory of the electronic device within the preset time period based on these characteristic positions in turn. In addition, after the characteristic positions corresponding to each target preset communication network are obtained, the electronic device can also output a location reminder message to prompt the user of the current location. Furthermore, functions such as arrival prediction are realized.

[0074] For example, the characteristic position corresponding to the preset communication network determined to match the first communication network is A station endpoint 1, the characteristic position corresponding to the preset communication network determined to match the second communication network is the middle of A platform, the characteristic position corresponding to the preset communication network determined to match the third communication network is A station endpoint 2, the characteristic position corresponding to the preset communication network determined to match the fourth communication network is between A and B stations, and the characteristic position corresponding to the preset communication network determined to match the fifth communication network is B station endpoint 1. Based on A station endpoint 1, the middle of A platform, A station endpoint 2, between A and B stations, and B station endpoint 1 in turn, the movement trajectory of the electronic device within the preset time period is generated as: A station endpoint 1 ~ the middle of A platform ~ A station endpoint 2 ~ between A and B stations ~ B station endpoint 1. Even if the 5G network on the subway line has a coverage range of only 50 to 100 meters, based on the radio frequency fingerprint map in this embodiment, it is still possible to more precisely and accurately determine the characteristic positions on the subway line, and these characteristic positions include the two endpoint areas of the platform, the area between the endpoints, and the area between stations, etc.

[0075] In the embodiments of the present application, when determining the movement trajectory of an electronic device within a preset time period based on the RF fingerprint information of each communication network, for each communication network, the cell identifier and signal strength information of the communication network are obtained from the RF fingerprint information of the communication network. The cell identifier and signal strength information of the communication network are matched with the cell identifier and signal strength information of the preset communication network in the preset RF fingerprint map to determine the preset communication network that matches each communication network. Based on the characteristic positions corresponding to each preset communication network, the movement trajectory of the electronic device within the preset time period is generated. Since the preset RF fingerprint map is used to represent the cell identifier and signal strength information of the preset communication network corresponding to each characteristic position on the movement route of the electronic device, therefore, the accuracy of the determined movement trajectory can be improved by combining the preset RF fingerprint map from two dimensions of the cell identifier and signal strength information, and it is not necessary to determine the movement trajectory of the electronic device through GPS.

[0076] In the previous embodiment, the process of determining the movement trajectory of an electronic device within a preset time period based on the RF fingerprint information of the communication network was described. In this embodiment, step 340 is further described in detail, which is to match the cell identifier and signal strength information of the communication network with the cell identifier and signal strength information of the preset communication network in the preset RF fingerprint map to determine the preset communication network that matches each communication network, including:

[0077] Match the cell identifier of the communication network with the preset cell identifier in the preset RF fingerprint map to determine the target cell identifier; the target cell identifier is the cell identifier with a successful match;

[0078] For each target cell identifier, match the signal strength information corresponding to the cell identifier of the communication network with the preset signal strength information corresponding to the target cell identifier in the preset RF fingerprint map to determine the target preset signal strength information; the target preset signal strength information is the preset signal strength information with a successful match;

[0079] Based on the target cell identifier and the target preset signal strength information, determine the preset communication network that matches each communication network.

[0080] First, match the cell identifier of the communication network with the cell identifier of the preset communication network in the preset RF fingerprint map to determine the cell identifier with a successful match as the target cell identifier. Second, for each target cell identifier, match the signal strength information corresponding to the cell identifier of the communication network with the signal strength information corresponding to the target cell identifier in the preset RF fingerprint map to determine the preset signal strength information with a successful match as the target preset signal strength information. Finally, use the preset communication network corresponding to the target cell identifier and the target preset signal strength information as the preset communication network that matches this communication network.

[0081] For each communication network connected to the electronic device within a preset time period, determine a preset communication network matching each communication network according to the cell identifier and signal strength information of each communication network.

[0082] For example, the cell identifier of the first communication network connected to the electronic device within the preset time period is obtained as: 1, and its signal strength information is: -110 to -100. Then, referring to Table 1-1, match the cell identifier of the communication network with the cell identifiers of the preset communication networks in the preset radio frequency fingerprint map to determine the successfully matched cell identifier as the target cell identifier. Here, the target cell identifier includes the cell identifier 1 corresponding to endpoint 1 of Station A, the cell identifier 1 corresponding to the middle of Platform A, the cell identifier 1 corresponding to endpoint 2 of Station A, the cell identifier 1 between Stations A and B, and the cell identifier 1 corresponding to endpoint 1 of Station B.

[0083] Furthermore, for each target cell identifier, match the signal strength information corresponding to the cell identifier of the communication network with the preset signal strength information corresponding to the target cell identifier in the preset radio frequency fingerprint map. For example, match the signal strength information -110 to -100 corresponding to the cell identifier 1 of the first communication network with the preset signal strength information corresponding to the target cell identifier 1 in the preset radio frequency fingerprint map. That is, match the signal strength information -110 to -100 with the preset signal strength information of the cell identifier 1 corresponding to endpoint 1 of Station A, the cell identifier 1 corresponding to the middle of Platform A, the cell identifier 1 corresponding to endpoint 2 of Station A, the cell identifier 1 between Stations A and B, and the cell identifier 1 corresponding to endpoint 1 of Station B, and filter out the preset signal strength information whose signal strength information is the same as or the difference is less than the preset difference threshold corresponding to the cell identifier of the communication network. It can be seen that the preset signal strength information of the cell identifier 1 corresponding to endpoint 1 of Station A is also -110 to -100, that is, determine the successfully matched preset signal strength information as the preset signal strength information corresponding to the cell identifier 1 at endpoint 1 of Station A.

[0084] Finally, based on the target cell identifier and the target preset signal strength information, determine the preset communication network matching each communication network. That is, determine that the preset communication network matching the first communication network is Cell 1 (cell identifier is 1) at endpoint 1 of Station A. Similarly, determine the preset communication networks matching each communication network in turn.

[0085] If the cell identifier of the second communication network connected to the electronic device within the preset time period is: 5, and its signal strength information is: -100 to -70. Then, referring to Table 1-1, determine that the target cell identifier is the cell identifier 5 corresponding to the middle of Platform A. Then, match the signal strength information -100 to -70 of the cell identifier 5 of the second communication network with the preset signal strength information corresponding to the target cell identifier 5 in the preset radio frequency fingerprint map. At this time, the preset signal strength information corresponding to the cell identifier 5 corresponding to the middle of Platform A happens to match it. Therefore, determine that the preset communication network matching the second communication network is the cell 5 corresponding to the middle of Platform A.

[0086] If the cell identifier of the third communication network connected to the electronic device within the preset time period is: 1, and its signal strength information is: -90 to -80. Then, referring to Table 1-1, determine that the target cell identifiers include the cell identifier 1 corresponding to Endpoint 1 of Platform A, the cell identifier 1 corresponding to the middle of Platform A, the cell identifier 1 corresponding to Endpoint 2 of Platform A, the cell identifier 1 corresponding to between Platforms A and B, and the cell identifier 1 corresponding to Endpoint 1 of Platform B. Then, match the signal strength information -100 to -70 of the cell identifier 1 of the third communication network with the preset signal strength information corresponding to the target cell identifier 1 in the preset radio frequency fingerprint map. At this time, the preset signal strength information corresponding to the cell identifier 1 of Endpoint 2 of Platform A happens to match it. Therefore, determine that the preset communication network matching the third communication network is the cell 1 corresponding to Endpoint 2 of Platform A.

[0087] In the embodiments of the present application, after obtaining the cell identifiers and signal strength information of each communication network connected to the electronic device within the preset time period, determine the preset communication network matching each communication network from two dimensions of the cell identifier and the signal strength information. Because a cell may cover multiple different characteristic locations, therefore, the preset communication network matching each communication network can be accurately determined from two dimensions of the cell identifier and the signal strength information. In the preset radio frequency fingerprint map, each preset communication network corresponds to a unique characteristic location. Therefore, based on the preset communication network matching each communication network and combining with the preset radio frequency fingerprint map, the movement trajectory of the electronic device within the preset time period can be determined.

[0088] Since it is not necessary to use GPS to determine the movement trajectory of the electronic device, the accuracy of the determined movement trajectory of the electronic device within the preset time period is higher and the applicable range is wider.

[0089] In the foregoing embodiments, it is introduced how to determine the preset communication network matching each communication network in combination with the preset radio frequency fingerprint map. In this embodiment, as Figure 6 shown, further introduce in detail step 360 of generating the movement trajectory of the electronic device within the preset time period based on the characteristic locations corresponding to each preset communication network, including:

[0090] Step 362: Obtain the characteristic positions corresponding to each preset communication network from the preset radio frequency fingerprint map, and generate a characteristic position sequence based on the characteristic positions corresponding to each preset communication network.

[0091] After determining the preset communication networks matching each communication network in terms of both cell identification and signal strength information, sequentially obtain the characteristic positions corresponding to each preset communication network from the preset radio frequency fingerprint map. Then, connect the characteristic positions corresponding to each preset communication network in sequence to generate the characteristic position sequence of the electronic device within the preset time period.

[0092] For example, assume that the preset communication network determined to match the first communication network is Cell 1 (cell identification is 1) at the end point 1 of Station A, the preset communication network determined to match the second communication network is Cell 5 corresponding to the middle of Station A platform, and the preset communication network determined to match the third communication network is Cell 1 corresponding to the end point 2 of Station A. Therefore, in combination with the preset radio frequency fingerprint map, the characteristic positions corresponding to each preset communication network can be determined to be End Point 1 of Station A, the middle of Station A platform, and End Point 2 of Station A in sequence. Furthermore, based on connecting these characteristic positions in sequence, the characteristic position sequence of the electronic device within the preset time period is generated as End Point 1 of Station A, the middle of Station A platform, and End Point 2 of Station A.

[0093] Step 364: Determine whether the characteristic position sequence meets the preset position sequence condition;

[0094] Step 366: If the characteristic position sequence meets the preset position sequence condition, use the characteristic position sequence as the movement track of the electronic device within the preset time period.

[0095] Because in the user's movement route, especially in the scenario of the user's commuting route to work (taking the subway), generally, the user moves forward continuously in one direction, so the characteristic positions passed by the user should also be continuous. After generating the characteristic position sequence of the electronic device within the preset time period, determine whether the characteristic position sequence meets the preset position sequence condition. Here, the preset position sequence condition includes that each characteristic position in the characteristic position sequence should be two adjacent characteristic positions.

[0096] Combined with Figure 7 As shown, it is a schematic diagram of the preset position sequence in an embodiment. Taking the subway scenario as an example, in one running direction, it sequentially includes Characteristic Position 1, Characteristic Position 2, Characteristic Position 3, Characteristic Position 4, Characteristic Position 5, Characteristic Position 6, Characteristic Position 7, Characteristic Position 8, Characteristic Position 9, Characteristic Position 10, and Characteristic Position 11. Figure 7In the text, POSX_Y represents the Y-th candidate position in the X-th positioning result. It can be known that the first positioning result and the third positioning result each have two candidate positions, and the second positioning result has 1 candidate position. Then, there are 4 characteristic position sequences for the three radio frequency fingerprint positioning results: (POS1_1, POS2_1, POS3_1), (POS1_1, POS2_1, POS3_2), (POS1_2, POS2_1, POS3_1), (POS1_2, POS2_1, POS3_2). For example, if the characteristic position sequence is (characteristic position 1, characteristic position 2, characteristic position 3), it is determined that the characteristic position sequence meets the preset position sequence condition, and it is considered that the movement trajectory of the electronic device within the preset time period is successfully obtained, and this characteristic position sequence is used as the movement trajectory of the electronic device within the preset time period. If the characteristic position sequence is (characteristic position 1, characteristic position 2, characteristic position 8), it is determined that the characteristic position sequence does not meet the preset position sequence condition, and it is considered that the movement trajectory of the electronic device within the preset time period is not successfully obtained.

[0097] In the embodiments of the present application, when generating the movement trajectory of the electronic device within the preset time period based on the characteristic positions corresponding to each preset communication network, a characteristic position sequence is generated based on the characteristic positions corresponding to each preset communication network. And the characteristic position sequence that meets the preset position sequence condition is used as the movement trajectory of the electronic device within the preset time period. By setting the preset position sequence condition, the correct movement trajectory can be screened out. Furthermore, the accuracy of subsequent network quality prediction for the electronic device based on the movement trajectory is improved.

[0098] In the foregoing embodiments, a detailed description is given of matching the radio frequency fingerprint information of each communication network with the preset radio frequency fingerprint map in turn to determine the movement trajectory of the electronic device within the preset time period. In this embodiment, as Figure 8 shown, a detailed description is continued for step 260, which is to perform quality prediction on the network to be connected by the electronic device during the prediction time period according to the movement trajectory and the preset network quality map, and generate a prediction result, including:

[0099] Step 262, determining whether the movement state of the electronic device is a stationary state or a moving state according to the movement trajectory.

[0100] Specifically, the cell identification and signal strength information of each communication network are matched with the cell identification and signal strength information of the preset communication network in the preset radio frequency fingerprint map to determine the preset communication network matched with each communication network. And after generating the movement trajectory of the electronic device within the preset time period based on the characteristic positions corresponding to each preset communication network, further determine whether the movement state of the electronic device is a stationary state or a moving state according to the movement trajectory of the electronic device within the preset time period.

[0101] Among them, the specific way to determine whether the motion state of the electronic device is a stationary state or a moving state can be determined based on the number of characteristic positions included in the motion trajectory of the electronic device within a preset time period. Specifically, if the motion trajectory includes one characteristic position, it is determined that the motion state of the electronic device is a stationary state. If the number of characteristic positions included in the motion trajectory is more than one, it is determined that the motion state of the electronic device is a moving state.

[0102] For example, the moving route of the electronic device can be the user's commuting route to work, and the user's commuting route to work can occur in a subway scenario. Then, if the motion trajectory of the electronic device within a preset time period only includes the endpoint 1 of Station A, it is determined that the motion state of the electronic device is a stationary state, that is, it is determined that the electronic device has been at the endpoint 1 of Station A within the preset time period. If the motion trajectory of the electronic device within a preset time period is endpoint 1 of Station A - middle of Platform A - endpoint 2 of Station A - between Stations A and B - endpoint 1 of Station B, it is determined that the number of characteristic positions included in the motion trajectory is more than one, that is, it is determined that the motion state of the electronic device is a moving state.

[0103] Step 264, if it is determined that the motion state of the electronic device is a stationary state, then based on the target characteristic position in the motion trajectory, combined with the preset radio frequency fingerprint map and the preset network quality map, predict the quality of the network to be connected by the electronic device during the prediction time period, and generate a first prediction result.

[0104] If the motion trajectory of the electronic device within a preset time period only includes one characteristic position, it is determined that the motion state of the electronic device is a stationary state within the preset time period. At this time, when predicting the quality of the network to be connected by the electronic device during the prediction time period, the network quality of the current communication network connected by the electronic device can be judged first. Because if the network quality of the current communication network connected by the electronic device is high, generally, if the electronic device continues to be in a stationary state, it will probably continue to maintain the connection with the current communication network. If the network quality of the current communication network connected by the electronic device is low, generally, if the electronic device continues to be in a stationary state, the electronic device will probably switch networks.

[0105] Then, the network quality parameters corresponding to the current communication network and the predicted time period can be found in the preset network quality map, and the network quality parameters can be used as the first prediction result. Specifically, the preset network quality map records the corresponding relationships between different preset communication networks, usage time periods, and the network quality parameters of the preset communication networks. Therefore, according to the current communication network accessed by the electronic device (such as the cell identifier being 1), the usage time period corresponding to the current communication network (such as the cell identifier being 1) and the network quality parameters of the preset communication network are obtained from the preset network quality map. Here, the network quality parameters include the network quality level and specific parameters. For example, the network quality level includes three levels: high, medium, and low. Of course, the present application does not limit this. The specific parameters can refer to any one or more of the download rate, delay, and packet loss rate.

[0106] Among them, the network quality prediction enabling condition can include that the application currently running on the electronic device is a preset application, and then the preset network quality map includes the first preset network quality map; the first preset network quality map is used to represent the corresponding relationships between the preset communication networks accessed by the electronic device when running the preset application on the moving route, the network quality parameters of the preset communication networks, the preset application, and the usage time period. For each application, the communication network is divided into different network quality levels based on the service requirements of the application. For example, for video or download applications, high download rates are required during data download so that the data can be loaded quickly. Therefore, for video or download applications, the network quality level of the communication network can be divided into three levels: high, medium, and low based on the download rate of the communication network; for live broadcast applications, low delay and low packet loss rate are required. Therefore, for live broadcast applications, the network quality level of the communication network can be divided into three levels: high, medium, and low based on the delay and packet loss rate of the communication network; for game or web browsing applications, low delay is required. Therefore, for game or web browsing applications, the network quality level of the communication network can be divided into three levels: high, medium, and low based on the delay of the communication network. Among them, the download rate can be calculated by the packet data received by different protocol layers per unit time. Taking the 5G communication network as an example, the download rate can be the download rate of any layer among the physical layer, MAC layer, RLC layer, PDCP layer, IP layer, TCP layer, UDP layer, and application layer. Of course, the present application does not limit this. Among them, the delay refers to the transmission time of data from the sending end to the receiving end, and the delay can be the delay of any layer among the application layer, TCP layer, and RLC layer. Of course, the present application does not limit this. Among them, the packet loss rate refers to the number of packets expected to be received but not received per unit time / the total number of packets expected to be received per unit time, and the packet loss rate can be the packet loss rate of any layer among the RLC layer, application layer, and TCP layer. Of course, the present application does not limit this.

[0107] Specifically, when classifying the network quality level of a communication network into three levels: high, medium, and low based on the download rate of the communication network, two download rate thresholds a and b can be set first, and a < b. If it is detected that the download rate of a video or download application under a certain communication network is less than a, it is considered that the network quality level of this communication network is the low level at this time; if it is detected that the download rate of a video or download application under a certain communication network is greater than or equal to a and less than b, it is considered that the network quality level of this communication network is the medium level at this time; correspondingly, if it is detected that the download rate of a video or download application under a certain communication network is greater than b, it is considered that the network quality level of this communication network is the high level at this time.

[0108] Specifically, according to the application X currently running on the electronic device and the current communication network (such as the cell identifier is 1), obtain the usage period and the network quality parameters of the preset communication network corresponding to the application X currently running on the electronic device and the current communication network (such as the cell identifier is 1) from the first preset network quality map. For example, the obtained usage period and network quality parameters of the preset communication network can be (period X, quality level - high, download rate 1), (period Y, quality level - medium, download rate 2), etc. Of course, the present application does not limit this.

[0109] Then, based on the prediction time period (such as period Y), from (period X, quality level - high, download rate 1), (period Y, quality level - medium, download rate 2), etc., obtain the network quality parameters (quality level - medium, download rate 2) corresponding to the prediction time period. At this time, the quality prediction of the network to be connected by the electronic device within the prediction time period is realized, and a first prediction result is generated, for example, (quality level - medium, download rate 2).

[0110] In the embodiment of the present application, first, determine the motion state of the electronic device as a stationary state or a moving state according to the motion trajectory. If it is determined that the motion state of the electronic device within the preset time period is a stationary state, when predicting the quality of the network to be connected by the electronic device within the prediction time period, the network quality of the current communication network connected by the electronic device can be judged first. Because if the network quality of the current communication network connected by the electronic device is relatively high, generally, if the electronic device continues to be in a stationary state, it will probably continue to maintain the connection with this current communication network. If the network quality of the current communication network connected by the electronic device is relatively low, generally, if the electronic device continues to be in a stationary state, the electronic device will probably perform a network switch.

[0111] Specifically, based on the current communication network, combined with the preset RF fingerprint map and the first preset network quality map, the quality of the network to be connected by the electronic device within the prediction time period can be predicted to generate a first prediction result.

[0112] In one embodiment, the network quality prediction enabling condition includes that the application currently running on the electronic device is a preset application.

[0113] Among them, the network quality prediction activation condition includes that the application currently running on the electronic device is a preset application. The preset application refers to an application that has high requirements for network quality. Here, the network quality can be represented by parameters such as download rate, data delay, packet loss rate, etc. Of course, this application does not limit the specific parameter types of network quality. A preset application list is stored on the electronic device, and the preset application list records the identifiers and related information of multiple preset applications. The preset application list can be generated by user pre-configuration, or the application can be added to the preset application list based on a joining request triggered by the application. The user can also add the application of interest to the preset application list in the interface settings. Of course, this application does not limit this. For example, preset applications include video or download applications, live broadcast applications, games or web browsing applications, etc., and this application does not limit this.

[0114] In the embodiment of the present application, when it is detected that the application currently running on the electronic device is a preset application, the network quality prediction process can be started to predict the network quality when the preset application is currently running on the electronic device. Based on the prediction results, migration to a high-quality network is achieved, thereby meeting the user's Internet access needs. It can also prevent the electronic device from always searching for signals in a low-quality network, thereby reducing the power consumption of the electronic device.

[0115] In one embodiment, the network quality prediction activation condition includes that the application currently running on the electronic device is a preset application, and the preset network quality map includes a first preset network quality map; the first preset network quality map is used to represent the correspondence between the preset communication network connected to the electronic device when the preset application is running on the mobile route, the network quality parameters of the preset communication network, the preset application, and the usage period. Figure 9 As shown, step 264 is described in detail. If it is determined that the motion state of the electronic device is a stationary state, a quality prediction is performed on the network to be connected to the electronic device within the prediction time period according to the target feature position in the motion trajectory combined with the preset radio frequency fingerprint map and the preset network quality map, and a first prediction result is generated, including:

[0116] Step 264a, obtaining network quality parameters of the current communication network to which the electronic device is connected.

[0117] Among them, the network quality prediction enabling condition includes that the application currently running on the electronic device is a preset application. The preset application refers to an application with high requirements for network quality. Here, the network quality can be represented by parameters such as download rate, data latency, packet loss rate, etc. Of course, the specific parameter types of the network quality in this application are not limited. A preset application list is stored on the electronic device, and the identification and related information of multiple preset applications are recorded in the preset application list. The preset application list can be generated by the user's pre-configuration, or an application can be added to the preset application list based on the join request triggered by the application, or the user can add the interested application to the preset application list in the interface settings. Of course, this application does not limit this.

[0118] Therefore, during the user's journey, first, it is judged whether the application currently running on the electronic device is a preset application. Specifically, it can be judged whether the identification of the currently running application is in the preset application list. If so, it is determined that the currently running application is a preset application, and the network quality prediction process is started; if not, it is determined that the currently running application is not a preset application, and the network quality prediction process is not started.

[0119] After starting the network quality prediction process, obtain the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period; determine the movement trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of each communication network. Determine the movement state of the electronic device as a stationary state or a moving state. If it is determined that the movement state of the electronic device is a stationary state at this time. And if the network quality of the current communication network connected to the electronic device is high, generally, if the electronic device continues to be in a stationary state, it may continue to maintain the connection with the current communication network. Because the movement state of the electronic device is a stationary state, when predicting the quality of the network to be connected by the electronic device within the prediction time period, the network quality of the current communication network connected to the electronic device can be judged first.

[0120] Specifically, obtain the network quality parameters of the current communication network to which the electronic device is connected, that is, obtain the network quality parameters corresponding to the cell identifier of the current communication network to which the electronic device is connected. Here, the network quality parameters may include parameters such as download rate, data delay, and packet loss rate. Since different types of application programs have different dependencies on each network quality parameter, for different types of application programs, the obtained network quality parameters of the current communication network may be different. For example, for video or download application programs, their dependence on the download rate is relatively high, and the obtained network quality parameters of the current communication network may be the download rate. For live broadcast application programs, their dependence on delay and packet loss rate is relatively high, and the obtained network quality parameters of the current communication network may be the delay and packet loss rate. For game or web browsing application programs, their dependence on delay is relatively high, and the obtained network quality parameters of the current communication network may be the delay. Of course, the present application does not make any limitations in this regard.

[0121] For example, if application program X is a video or download application program, then application program X has a relatively high dependence on the download rate, and the obtained network quality parameters of the current communication network may be the download rate.

[0122] Step 264b, determine whether the network quality parameters of the current communication network are lower than the preset network quality threshold.

[0123] After obtaining the network quality parameters of the current communication network to which the electronic device is connected, determine whether the network quality parameters of the current communication network are lower than the preset network quality threshold. Here, the preset network quality threshold may be obtained based on the network quality parameters of the application program currently running on the electronic device during normal operation. Taking the network quality parameter as the download rate as an example, the preset network quality threshold here may include at least two preset thresholds. For example, during the process of obtaining the download rate of the current communication network, after detecting that the download rate reaches the preset threshold thres2, continue to detect whether the download rate drops below thres1 within the preset time t. If the above two conditions are met, that is, the network quality parameters of the current communication network are higher than the preset network quality threshold, it is considered that the cell corresponding to the current communication network is a cell with relatively high communication quality, that is, it is concluded that the communication quality level of the cell corresponding to the current communication network is a high level. If the network quality parameters of the current communication network are equal to the preset network quality threshold, it is considered that the cell corresponding to the current communication network is a cell with medium-level communication quality, that is, it is concluded that the communication quality level of the cell corresponding to the current communication network is a medium level. On the contrary, if the above two conditions are not met or only one of them is met, that is, the network quality parameters of the current communication network are lower than the preset network quality threshold, it is considered that the cell corresponding to the current communication network is a cell with relatively low communication quality, that is, it is concluded that the communication quality level of the cell corresponding to the current communication network is a low level.

[0124] Step 264c: If the network quality parameter of the current communication network is lower than the preset network quality threshold, then based on the target feature positions in the motion trajectory, in combination with the preset radio frequency fingerprint map and the first preset network quality map, perform quality prediction on the network to be connected by the electronic device during the prediction time period, and generate a first prediction result.

[0125] Specifically, the network quality prediction enabling condition includes that the application currently running on the electronic device is a preset application, and the preset network quality map includes the first preset network quality map. Among them, the first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running the preset application on the moving route, the network quality parameter of the preset communication network, the preset application, and the usage period.

[0126] If the network quality parameter of the current communication network is higher than the preset network quality threshold, it is considered that the cell corresponding to the current communication network is a cell with relatively high communication quality, that is, it is concluded that the communication quality level of the cell corresponding to the current communication network is a high level. At this time, it shows that the current communication network can meet the service requirements of the application currently running on the electronic device. Because the motion state of the electronic device is a stationary state and the current communication network can meet the service requirements of the application currently running on the electronic device, the electronic device can continue to connect to the current communication network during the prediction time period. Therefore, the quality of the network to be connected by the electronic device during the prediction time period can be directly predicted, and it is concluded that the communication quality level of the network to be connected by the electronic device is a high level.

[0127] If the network quality parameter of the current communication network is lower than the preset network quality threshold, it is considered that the cell corresponding to the current communication network is a cell with relatively low communication quality, that is, it is concluded that the communication quality level of the cell corresponding to the current communication network is a low level. Then, during the prediction time period, the electronic device will look for a network with a relatively high communication quality level to connect to, that is, the preset communication network accessed by the electronic device during the prediction time period may be different from the current communication network. Therefore, it is necessary to perform quality prediction on the network to be connected by the electronic device during the prediction time period.

[0128] Specifically, based on the target feature positions in the movement trajectory, in combination with a preset radio frequency fingerprint map and a first preset network quality map, the network quality of the network to be connected by the electronic device during the prediction time period is predicted to generate a first prediction result. The first candidate communication network set corresponding to the target feature positions can be determined based on the target feature positions in the movement trajectory in combination with the preset radio frequency fingerprint map. If there is a communication network with a high-level communication quality level in the first candidate communication network set determined based on the first preset network quality map, it can be concluded that the network quality of the network to be connected by the electronic device during the prediction time period is high level, and the high-level network quality is used as the first prediction result. If there is a communication network with a medium-level communication quality level in the first candidate communication network set determined based on the first preset network quality map, it can be concluded that the network quality of the network to be connected by the electronic device during the prediction time period is medium level, and the medium-level network quality is used as the first prediction result. Similarly, if there is a communication network with a low-level communication quality level in the first candidate communication network set determined based on the first preset network quality map, it can be concluded that the network quality of the network to be connected by the electronic device during the prediction time period is low level, and the low-level network quality is used as the first prediction result.

[0129] Among them, the first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running a preset application program on the movement route, the network quality parameters of the preset communication network, the preset application program, and the usage period. Here, the preset application programs include application program X, application program Y, application program Z, etc., and the present application does not limit this. Here, the usage period can be different usage periods every day, such as 7:55AM - 8:00AM, 8:00AM - 8:05AM, 2:00PM - 4:00PM, 5:30PM - 6:00PM, etc. Here, the network quality parameters include the network quality level and specific parameters. For example, the network quality level includes three levels: high, medium, and low. Of course, the present application does not limit this. The specific parameters can refer to any one or more of the download rate, delay, and packet loss rate.

[0130] Therefore, the first preset network quality map records the corresponding relationship between the cell identifiers of different preset communication networks, the preset application programs, the usage period, and the network quality parameters of the preset communication networks. A partial data table corresponding to the first preset network quality map is shown in Table 1-2 below:

[0131] Table 1-2

[0132]

[0133]

[0134] Assume that the prediction time period is time period X. If the cell identifier of the current communication network is 1, the network quality parameters corresponding to the current communication network (cell identifier 1), the prediction time period (time period X), and the preset application X can be found from the first preset network quality map as (high quality level, parameter 1). Then, the network quality parameters (high quality level, network parameter 1) are used as the first prediction result of the network prediction. Of course, the above is only an example, and this application does not make any limitations in this regard.

[0135] In the embodiments of this application, if it is determined that the motion state of the electronic device is a stationary state, the network quality parameters of the current communication network connected to the electronic device are obtained, and it is determined whether the network quality parameters of the current communication network are lower than the preset network quality threshold. If the network quality parameters of the current communication network are lower than the preset network quality threshold, then based on the target feature positions in the motion trajectory, in combination with the preset radio frequency fingerprint map and the first preset network quality map, the quality of the network to be connected by the electronic device during the prediction time period is predicted to generate a first prediction result.

[0136] When predicting the quality of the network to be connected by the electronic device during the prediction time period, the network quality of the current communication network connected to the electronic device can be determined first. Since the motion state of the electronic device is a stationary state, if the network quality of the current communication network connected to the electronic device is at a high level, the first prediction result can be directly obtained as a high level. If the network quality of the current communication network connected to the electronic device is at a low level, then during the prediction time period, the electronic device will look for a network with a higher communication quality level to connect. Therefore, it is necessary to predict the quality of the network to be connected by the electronic device during the prediction time period based on the target feature positions in the motion trajectory, in combination with the preset radio frequency fingerprint map and the first preset network quality map, to generate a first prediction result. When the network quality of the current communication network connected to the electronic device is at a low level, predicting the quality of the network to be connected by the electronic device during the prediction time period based on the target feature positions in the motion trajectory, in combination with the preset radio frequency fingerprint map and the first preset network quality map, can predict the process of the electronic device looking for a network with a higher communication quality level, thereby improving the accuracy of network quality prediction.

[0137] In the previous embodiment, the process of predicting the quality of the network to be connected by the electronic device during the prediction time period and generating a first prediction result when it is determined that the motion state of the electronic device is a stationary state is described. In this embodiment, as Figure 10As shown, specifically when the electronic device is in a stationary state and whether the network quality parameter of the current communication network is lower than the preset network quality threshold, step 264c details the process of predicting the quality of the network to be connected by the electronic device during the prediction time period based on the target feature positions in the movement trajectory, in combination with the preset radio frequency fingerprint map and the first preset network quality map, to generate the first prediction result, including:

[0138] Step 1020, output a first prompt message, which is used to prompt that the electronic device has accessed a communication network with a network quality parameter lower than the preset network quality threshold.

[0139] If the network quality parameter of the current communication network is lower than the preset network quality threshold, it is considered that the cell corresponding to the current communication network is a cell with relatively low communication quality, that is, the communication quality level of the cell corresponding to the current communication network is a low level. At this time, the electronic device first outputs a first prompt message, which is used to prompt that the electronic device has accessed a communication network with a network quality parameter lower than the preset network quality threshold.

[0140] Step 1040, find a first candidate communication network set corresponding to the target feature position from the preset radio frequency fingerprint map.

[0141] Then, based on the target feature positions in the movement trajectory of the electronic device, find a first candidate communication network set corresponding to the target feature position from the preset radio frequency fingerprint map. Here, if the electronic device is in a stationary state, the target feature position is the current feature position of the electronic device. Among them, the preset radio frequency fingerprint map records the radio frequency fingerprint information of the preset communication networks accessed by the electronic device at each feature position on the movement route. Here, the preset radio frequency fingerprint map can be stored in the database in the form of a data table. Suppose that on the user's commuting route to work (such as from subway station A - subway station B - subway station C), that is, at this time the movement route of the electronic device is the same as the commuting route to work. At this time, a partial data table corresponding to the preset radio frequency fingerprint map is shown in Table 1-1 above.

[0142] Suppose that the target feature position in the movement trajectory of the electronic device is the end point 1 of station A. Then, in combination with the preset radio frequency fingerprint map, the first candidate communication network set corresponding to the target feature position can be obtained as [cell identifier 1, cell identifier 2]. Suppose that the target feature position in the movement trajectory of the electronic device is the middle of platform A. Then, in combination with the preset radio frequency fingerprint map, the first candidate communication network set corresponding to the target feature position can be obtained as [cell identifier 1, cell identifier 5].

[0143] Step 1060: Search for the first candidate network quality parameters corresponding to the first candidate communication network set, the predicted time period, and the preset application program in the first preset network quality map, and generate a first prediction result based on the first candidate network quality parameters.

[0144] After obtaining the first candidate communication network set corresponding to the target feature location, search for the first candidate network quality parameters corresponding to the first candidate communication network set, the predicted time period, and the preset application program in the first preset network quality map, and generate a first prediction result based on the first candidate network quality parameters. Among them, the first preset network quality map records the corresponding relationship between the cell identifiers of different preset communication networks, the preset application program, the usage period, and the network quality parameters of the preset communication network. A partial data table corresponding to the first preset network quality map can be combined as shown in Table 1-2 above.

[0145] Suppose that at this time, the preset application program X is running on the electronic device, and the target feature location in the movement trajectory of the electronic device is the endpoint 1 of Station A. Then, in combination with the preset radio frequency fingerprint map, the first candidate communication network set corresponding to the target feature location can be obtained as [cell identifier 1, cell identifier 2]. Suppose the predicted time period is period Y again, then search for the network quality parameters corresponding to the first candidate communication network set [cell identifier 1, cell identifier 2], the predicted time period Y, and the preset application program X in the first preset network quality map. At this time, the network quality parameters corresponding to the obtained cell identifier 1 are (in the medium quality level, network parameter 2), and the network quality parameters corresponding to the obtained cell identifier 2 are (in the high quality level, network parameter 2).

[0146] Then, at this time, a first prediction result can be generated based on the first candidate network quality parameters. Specifically, assume that there is a communication network with a high quality level in the first candidate communication network set. Therefore, a first prediction result can be generated based on the high-level communication network. That is, the first prediction result is that the network quality of the electronic device during the predicted time period can be at a high level. Assume that there is no communication network with a high quality level in the first candidate communication network set, but there is a communication network with a medium quality level. Then, a first prediction result can be generated based on this medium-level communication network. That is, the first prediction result is that the network quality of the electronic device during the predicted time period can be at a medium level.

[0147] In an embodiment of the present application, when the motion state of the electronic device is in a stationary state and if the network quality parameter of the current communication network is lower than the preset network quality threshold, first, a first prompt message is output, and the first prompt message is used to prompt that the electronic device has accessed a communication network with a network quality parameter lower than the preset network quality threshold. Secondly, a first candidate communication network set corresponding to the target feature position is searched from the preset radio frequency fingerprint map. Finally, a first candidate network quality parameter corresponding to the first candidate communication network set, the prediction time period, and the preset application program is searched from the first preset network quality map, and a first prediction result is generated according to the first candidate network quality parameter.

[0148] On the one hand, the first prompt message is output to prompt that the electronic device has accessed a communication network with a network quality parameter lower than the preset network quality threshold at this time. On the other hand, a first candidate communication network set corresponding to the target feature position is searched from the preset radio frequency fingerprint map. The electronic device can be connected to each communication network in the first candidate communication network set during the prediction time period. Therefore, the first prediction result can be accurately determined based on each communication network in the first candidate communication network set.

[0149] Continuing from the previous, in one embodiment, a network quality prediction method is provided, which further includes:

[0150] If the first prediction result is that there is a first target communication network in the first candidate communication network set with a network quality level higher than or equal to the preset network quality level, then switch from the current communication network to the first target communication network.

[0151] Specifically, a first candidate communication network set corresponding to the target feature position is searched from the preset radio frequency fingerprint map. Then, a first candidate network quality parameter corresponding to the first candidate communication network set, the prediction time period, and the preset application program is searched from the first preset network quality map, and a first prediction result is generated according to the first candidate network quality parameter.

[0152] Judge whether the first prediction result is that there is a first target communication network in the first candidate communication network set with a network quality level higher than or equal to the preset network quality level. If so, switch from the current communication network to the first target communication network. Here, the preset network quality level can be a low level. If it is judged that there is a first target communication network in the first candidate communication network set with a network quality level higher than or equal to the low level, that is, it is judged that there is a first target communication network with a high level or a medium level in the first candidate communication network set, then switch from the current communication network to the first target communication network with a high level or a medium level. Among them, the first target communication network includes a communication network based on the fifth-generation mobile communication technology 5G or a communication network based on the sixth-generation mobile communication technology 6G, and the present application does not make any limitations in this regard.

[0153] In an embodiment of the present application, if the first prediction result is that there is a first target communication network in the first candidate communication network set with a network quality level higher than or equal to a preset network quality level, the electronic device switches from the current communication network to the first target communication network. During the prediction time period, the electronic device will search for a communication network with a higher communication quality for connection. If there is a first target communication network in the first candidate communication network set with a network quality level higher than or equal to the preset network quality level, the electronic device will switch from connecting to the current communication network to connecting to the first target communication network during the prediction time period. Thus, a better communication network can be provided for the electronic device.

[0154] In the foregoing embodiment, the process of predicting the quality of the network to be connected by the electronic device during the prediction time period and generating the first prediction result when the motion state of the electronic device is a stationary state is described. In this embodiment, the network quality prediction enabling condition includes that the application program currently running on the electronic device is a preset application program, and the preset network quality map includes a first preset network quality map; the first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running the preset application program on the moving route, the network quality parameters of the preset communication network, the preset application program, and the usage period. As Figure 11 shown, the process of predicting the quality of the network to be connected by the electronic device during the prediction time period and generating the second prediction result when the motion state of the electronic device is a moving state is described in detail, including:

[0155] Step 1120, if it is determined that the motion state of the electronic device is a moving state, obtain the current feature position in the motion trajectory and at least one predicted feature position along the forward direction of the motion trajectory.

[0156] Specifically, match the cell identification and signal strength information of each communication network with the cell identification and signal strength information of the preset communication network in the preset radio frequency fingerprint map to determine the preset communication network matched with each communication network. And after generating the motion trajectory of the electronic device within the preset time period based on the feature positions corresponding to each preset communication network, further determine whether the motion state of the electronic device is a stationary state or a moving state according to the motion trajectory of the electronic device within the preset time period.

[0157] Among them, the specific method for determining whether the motion state of the electronic device is a stationary state or a moving state can be determined based on the number of feature positions included in the motion trajectory of the electronic device within the preset time period. Specifically, if the motion trajectory includes one feature position, it is determined that the motion state of the electronic device is a stationary state. If the number of feature positions included in the motion trajectory is more than one, it is determined that the motion state of the electronic device is a moving state.

[0158] If it is determined that the motion state of the electronic device is a moving state, the current feature position in the motion trajectory and at least one predicted feature position along the forward direction of the motion trajectory are obtained.

[0159] For example, the moving route of the electronic device can be the user's commuting route to work, and the user's commuting route to work can occur in a subway scenario. If the motion trajectory of the electronic device within a preset time period is from the end point 1 of Station A to the middle of Platform A of Station A, it is determined that the number of feature positions included in the motion trajectory is more than one, that is, it is determined that the motion state of the electronic device is a moving state. Further, the current feature position in the motion trajectory and at least one predicted feature position along the forward direction of the motion trajectory are obtained. At this time, the current feature position obtained in the motion trajectory is the end point 1 of Station A. And it is determined that the forward direction of the motion trajectory of the electronic device is from Platform A to Platform B, then at least one predicted feature position along the forward direction of the motion trajectory is obtained. For example, obtaining at least one predicted feature position along the forward direction of the motion trajectory includes the end point 2 of Station A - between Stations A and B - the end point 1 of Station B, or includes the end point 2 of Station A, between Stations A and B, or only includes the end point 2 of Station A. Of course, the present application does not make any limitations in this regard.

[0160] Step 1140: Based on the current feature position and at least one predicted feature position, in combination with a preset radio frequency fingerprint map and a first preset network quality map, predict the quality of the network to be connected by the electronic device during the predicted time period, and generate a second prediction result.

[0161] The network quality prediction enabling condition includes that the application currently running on the electronic device is a preset application, and the preset network quality map includes a first preset network quality map. The first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running the preset application on the moving route, the network quality parameters of the preset communication network, the preset application, and the usage period.

[0162] Based on the current feature location and at least one predicted feature location, in combination with a preset radio frequency fingerprint map, a second candidate communication network set corresponding to the current feature location and the at least one predicted feature location can be determined. If it is determined based on the first preset network quality map that there is a communication network with a high-level communication quality in the second candidate communication network set, it can be concluded that the network quality of the network to be connected by the electronic device during the predicted time period is high level, and the high-level network quality is used as the second prediction result. If it is determined based on the first preset network quality map that there is a communication network with a medium-level communication quality in the second candidate communication network set, it can be concluded that the network quality of the network to be connected by the electronic device during the predicted time period is medium level, and the medium-level network quality is used as the second prediction result. Similarly, if it is determined based on the first preset network quality map that there is a communication network with a low-level communication quality in the second candidate communication network set, it can be concluded that the network quality of the network to be connected by the electronic device during the predicted time period is low level, and the low-level network quality is used as the second prediction result.

[0163] Among them, the first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running a preset application program on the moving route, the network quality parameters of the preset communication network, the preset application program, and the usage period. Here, the preset application programs include application program X, application program Y, application program Z, etc., and the present application does not limit this. Here, the usage period can be different usage periods every day, such as 7:55 AM - 8:00 AM, 8:00 AM - 8:05 AM, 2:00 PM - 4:00 PM, 5:30 PM - 6:00 PM, etc. Here, the network quality parameters include the network quality level and specific parameters. For example, the network quality level includes three levels: high, medium, and low. Of course, the present application does not limit this. The specific parameters can refer to any one or more of the download rate, delay, and packet loss rate.

[0164] Therefore, the first preset network quality map records the corresponding relationship between the cell identifiers of different preset communication networks, the preset application program, the usage period, and the network quality parameters of the preset communication network. A partial data table corresponding to the first preset network quality map is shown in Table 1-2 above.

[0165] In an embodiment of the present application, if it is determined that the motion state of the electronic device is a moving state, the current feature position in the motion trajectory and at least one predicted feature position along the forward direction of the motion trajectory are obtained. Based on the current feature position and at least one predicted feature position, in combination with a preset radio frequency fingerprint map and a first preset network quality map, the network quality of the network to be connected by the electronic device during the predicted time period is predicted to generate a second prediction result. Based on the current feature position and at least one predicted feature position in combination with the preset radio frequency fingerprint map, a plurality of preset communication networks corresponding to the current feature position and at least one predicted feature position can be determined. Since the first preset network quality map records the correspondence between the cell identifiers of different preset communication networks, preset application programs, usage time periods, and network quality parameters of the preset communication networks, based on the plurality of preset communication networks in combination with the first preset network quality map, the network quality of the network to be connected by the electronic device during the predicted time period can be predicted. Furthermore, the accuracy of predicting the network quality of the network to be connected by the electronic device during the predicted time period is improved.

[0166] In the previous embodiment, it was described how to predict the network quality of the network to be connected by the electronic device during the predicted time period if it is determined that the motion state of the electronic device is a moving state. As Figure 12 shown, in this embodiment, step 1140, based on the current feature position and at least one predicted feature position, in combination with a preset radio frequency fingerprint map and a first preset network quality map, predicting the network quality of the network to be connected by the electronic device during the predicted time period to generate a second prediction result is described in detail, including:

[0167] Step 1142, searching in the preset radio frequency fingerprint map for a second candidate communication network set corresponding to the current feature position and at least one predicted feature position.

[0168] Among them, the preset radio frequency fingerprint map records the radio frequency fingerprint information of the preset communication networks accessed by the electronic device at each feature position on the moving route, and the radio frequency fingerprint information includes cell identifiers and signal strength information. Combining Table 1-1, the preset communication networks accessed by the electronic device corresponding to the current feature position and at least one predicted feature position can be searched in the preset radio frequency fingerprint map. Based on the preset communication networks accessed by the electronic device corresponding to the current feature position and at least one predicted feature position, a second candidate communication network set is formed.

[0169] For example, the current feature position in the motion trajectory is obtained as the end point 1 of Station A. And it is determined that the forward direction of the motion trajectory of the electronic device is from Station A to Station B. Then, obtaining at least one predicted feature position along the forward direction of the motion trajectory includes the end point 2 of Station A and the section between Stations A and B. The preset communication networks accessed by the electronic device corresponding to the end point 2 of Station A can be found from the preset RF fingerprint map as: Cell 1 and Cell 8; the preset communication networks accessed by the electronic device corresponding to the section between Stations A and B are: Cell 1 and Cell 12. Based on Cell 1, Cell 8, and Cell 12, a second candidate communication network set is formed.

[0170] Step 1144, find the second candidate network quality parameters corresponding to the second candidate communication network set, the predicted time period, and the preset application program from the first preset network quality map, and generate a second prediction result according to the second candidate network quality parameters.

[0171] Since the first preset network quality map records the correspondence between the cell identifiers of different preset communication networks, the preset application program, the usage period, and the network quality parameters of the preset communication networks, therefore, the second candidate network quality parameters corresponding to the second candidate communication network set, the predicted time period, and the preset application program can be found from the first preset network quality map, and a second prediction result is generated according to the second candidate network quality parameters. For example, assume that the preset application program is Application Program X, the predicted time period is Time Period X, and the second candidate communication network set includes Cell 1, Cell 8, and Cell 12. The network quality parameters corresponding to the second candidate communication network set, the predicted time period, and the preset application program can be found from the first preset network quality map as: the quality level of Cell 1 in Time Period X is high level; the quality level of Cell 8 in Time Period X is low level; the quality level of Cell 12 in Time Period X is low level. Finally, a second prediction result is generated according to the second candidate network quality parameters. Specifically, assume that there is a communication network with a high quality level in the second candidate communication network set. Therefore, a second prediction result can be generated based on the communication network with a high level. That is, the second prediction result is that the network quality of the electronic device in the predicted time period can be at a high level. Assume that there is no communication network with a high quality level in the second candidate communication network set, but there is a communication network with a medium quality level. Then, a second prediction result can be generated based on the communication network with a medium level. That is, the second prediction result is that the network quality of the electronic device in the predicted time period can be at a medium level. Assume that there is no communication network with a high quality level in the second candidate communication network set, but there is a communication network with a low quality level. Then, a second prediction result can be generated based on the communication network with a low level. That is, the second prediction result is that the network quality of the electronic device in the predicted time period can be at a low level.

[0172] For example, according to the network quality parameters: the quality level of cell 1 in time period X is high; the quality level of cell 8 in time period X is low; the quality level of cell 12 in time period X is low, it can be obtained that the second prediction result is that the network quality of the electronic device during the prediction time period can be high level.

[0173] In the embodiments of the present application, when it is determined that the motion state of the electronic device is a moving state, first, a second candidate communication network set corresponding to the current feature position and at least one predicted feature position is searched from the preset radio frequency fingerprint map. Secondly, second candidate network quality parameters corresponding to the second candidate communication network set, the prediction time period, and the preset application program are searched from the first preset network quality map, and a second prediction result is generated according to the second candidate network quality parameters.

[0174] Since the electronic device can be connected to each communication network in the second candidate communication network set during the prediction time period, therefore, the second prediction result can be accurately determined based on each communication network in the second candidate communication network set.

[0175] In one embodiment, as Figure 13 shown, if the second candidate network quality parameters include a second candidate communication network in the second candidate communication network set whose network quality parameter is lower than the preset network quality threshold, a network quality prediction method is provided, and it further includes:

[0176] Step 1320, output a second prompt message, where the second prompt message is used to prompt that the electronic device is about to access a second candidate communication network whose network quality parameter is lower than the preset network quality threshold.

[0177] If there is a second candidate communication network in the second candidate communication network set whose network quality parameter is lower than the preset network quality threshold, then during the prediction time period, the electronic device may access a second candidate communication network whose network quality parameter is lower than the preset network quality threshold. Therefore, the electronic device first outputs a second prompt message, and the second prompt message is used to prompt that the electronic device is about to access a second candidate communication network whose network quality parameter is lower than the preset network quality threshold.

[0178] For example, in the second candidate communication network set, the quality level of cell 1 in time period X is high, the quality level of cell 8 in time period X is low, and the quality level of cell 12 in time period X is low. Therefore, it can be concluded that there is a second candidate communication network in the second candidate communication network set whose network quality parameter is lower than the preset network quality threshold. At this time, a second prompt message is output, and the second prompt message is used to prompt that the electronic device is about to access a second candidate communication network whose network quality parameter is lower than the preset network quality threshold.

[0179] Step 1340: Determine whether there is a second target communication network in the second candidate communication network whose network quality parameter is higher than or equal to the preset network quality threshold.

[0180] Then, determine whether there is a second target communication network in the second candidate communication network whose network quality parameter is higher than or equal to the preset network quality threshold. For example, in the second candidate communication network set, the quality level of cell 1 at time period X is high, the quality level of cell 8 at time period X is low, and the quality level of cell 12 at time period X is low. Therefore, it can be concluded that there is a second candidate communication network in the second candidate communication network set whose network quality parameter is higher than or equal to the preset network quality threshold.

[0181] Step 1360: If there is a second target communication network, when it is detected that the electronic device accesses a communication network with a network quality parameter lower than the preset network quality threshold, switch to the second target communication network.

[0182] After determining whether there is a second target communication network in the second candidate communication network whose network quality parameter is higher than or equal to the preset network quality threshold, and it is determined that there is a second target communication network in the second candidate communication network, then it is detected in real time whether the electronic device accesses a communication network with a network quality parameter lower than the preset network quality threshold (that is, whether it accesses a preset network with a low level).

[0183] If it is detected that the electronic device accesses a communication network with a network quality parameter lower than the preset network quality threshold, since there is a second target communication network in the second candidate communication network whose network quality parameter is higher than or equal to the preset network quality threshold, therefore, the electronic device can switch to the second target communication network to provide a better communication network for the electronic device. Among them, the second target communication network includes a communication network based on the fifth-generation mobile communication technology 5G or a communication network based on the sixth-generation mobile communication technology 6G, and this application does not make a limitation on this.

[0184] In the embodiment of this application, if there is a second candidate communication network in the second candidate communication network set whose network quality parameter is lower than the preset network quality threshold, a network quality prediction method is also provided, which further includes: First, output a second prompt message, and the second prompt message is used to prompt that the electronic device is about to access a communication network with a network quality parameter lower than the preset network quality threshold. Second, determine whether there is a second target communication network in the second candidate communication network whose network quality parameter is higher than or equal to the preset network quality threshold. If there is a second target communication network, when it is detected that the electronic device accesses a communication network with a network quality parameter lower than the preset network quality threshold, switch to the second target communication network.

[0185] On the one hand, a second prompt message is output to prompt that the electronic device is about to access a communication network whose network quality parameter is lower than a preset network quality threshold. On the other hand, since there is a second target communication network in the second candidate communication networks whose network quality parameter is higher than or equal to the preset network quality threshold, when it is detected that the electronic device accesses a communication network whose network quality parameter is lower than the preset network quality threshold, the electronic device can switch to the second target communication network to provide a better communication network for the electronic device.

[0186] In one embodiment, a network quality prediction method is provided, which further includes:

[0187] For each preset application, obtain the preset communication network, usage period, and network quality parameter of the preset communication network to which the electronic device is connected when running the preset application on the moving route.

[0188] Here, the moving route can be the user's commuting route to work. Therefore, for each preset application, the preset communication network to which the electronic device is connected when running the preset application on the user's commuting route to work, as well as the usage period and the network quality parameter of the preset communication network can be obtained.

[0189] For example, it is obtained that the preset communication network (cell 1) to which the electronic device is connected when running application X on the user's commuting route to work, as well as the usage periods (period X, period Y) and the network quality parameter of the preset communication network (cell 1). It is obtained that the preset communication network (cell 2) to which the electronic device is connected when running application X on the user's commuting route to work, as well as the usage periods (period X, period Y) and the network quality parameter of the preset communication network (cell 2)...... and so on. It is obtained that each preset communication network to which the electronic device is connected when running application X on the user's commuting route to work, as well as the usage period and the network quality parameter of each preset communication network.

[0190] Generate a first preset network quality map based on the preset communication network, usage period, and network quality parameter of the preset communication network corresponding to each preset application.

[0191] After, for each preset application, it is obtained that each preset communication network to which the electronic device is connected when running the preset application on the user's commuting route to work, as well as the usage period and the network quality parameter of each preset communication network, a first preset network quality map can be generated based on the preset communication network, usage period, and network quality parameter of the preset communication network corresponding to each preset application. Specifically, as shown in Table 1-2, it is a partial data table corresponding to the first preset network quality map in one embodiment.

[0192] In the embodiments of the present application, for each preset application, the preset communication network, usage period, and network quality parameters of the preset communication network connected when the electronic device runs the preset application on the movement route are obtained. Then, based on the preset communication network, usage period, and network quality parameters of the preset communication network corresponding to each preset application, a first preset network quality map is generated. Subsequently, according to the movement trajectory and the first preset network quality map, the quality of the network to be connected by the electronic device during the prediction time period can be predicted to generate a prediction result. Furthermore, the accuracy of predicting the quality of the network to be connected by the electronic device during the prediction time period is improved.

[0193] In a specific embodiment, as Figure 14 shown, a network quality prediction method is provided, including:

[0194] Step 1402, determine whether the application currently running on the electronic device is a preset application; if so, proceed to step 1404; if not, proceed to step 1430;

[0195] Step 1404, obtain the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period;

[0196] Step 1406, for each communication network, obtain the cell identifier and signal strength information of the communication network from the radio frequency fingerprint information of the communication network;

[0197] Step 1408, match the cell identifier and signal strength information of the communication network with the cell identifier and signal strength information of the preset communication network in the preset radio frequency fingerprint map to determine the preset communication network matched with each communication network;

[0198] Step 1410, obtain the characteristic positions corresponding to each preset communication network from the preset radio frequency fingerprint map, and generate a characteristic position sequence based on the characteristic positions corresponding to each preset communication network;

[0199] Step 1412, determine whether the characteristic position sequence meets the preset position sequence condition; if so, proceed to step 1414; if not, proceed to step 1430;

[0200] Step 1414, if the characteristic position sequence meets the preset position sequence condition, use the characteristic position sequence as the movement trajectory of the electronic device within the preset time period.

[0201] Step 1416, determine the movement state of the electronic device as a stationary state or a moving state according to the movement trajectory; if it is a stationary state, proceed to step 1418; if it is a moving state, proceed to step 1424;

[0202] Step 1418, obtain the network quality parameters of the current communication network connected to the electronic device;

[0203] Step 1420: Determine whether the network quality parameter of the current communication network is lower than a preset network quality threshold; if so, proceed to Step 1422; if not, proceed to Step 1430;

[0204] Step 1422: Based on the target feature positions in the movement trajectory, in combination with a preset radio frequency fingerprint map and a first preset network quality map, perform quality prediction on the network to be connected by the electronic device during the prediction time period, and generate a first prediction result;

[0205] Step 1424: Obtain the current feature position in the movement trajectory and at least one predicted feature position along the forward direction of the movement trajectory;

[0206] Step 1426: Search in the preset radio frequency fingerprint map for a second candidate communication network set corresponding to the current feature position and at least one predicted feature position;

[0207] Step 1428: Search in the first preset network quality map for second candidate network quality parameters corresponding to the second candidate communication network set, the prediction time period, and a preset application program, and generate a second prediction result based on the second candidate network quality parameters;

[0208] Step 1430: End.

[0209] In an embodiment of the present application, radio frequency fingerprint information of a communication network connected to an electronic device within a preset time period is obtained. Since the current position of the electronic device can be identified by recognizing the radio frequency fingerprint information of the communication network, the movement trajectory of the electronic device within the preset time period can be determined based on the radio frequency fingerprint information of each communication network connected to the electronic device within the preset time period. On the one hand, it is not necessary to use GPS to determine the movement trajectory of the electronic device, so it can be applied to scenarios where a GPS signal cannot be obtained or cannot be accurately obtained. On the other hand, since the first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running a preset application program on the movement route, the network quality parameter of the preset communication network, the preset application program, and the usage period. Therefore, based on the current position of the electronic device on the movement route, the predicted trajectory of the electronic device during the prediction time period is further determined, and then the preset communication network corresponding to the predicted trajectory and the network quality of the preset communication network can be accurately determined from the first preset network quality map. Finally, quality prediction of the network to be connected by the electronic device during the prediction time period is achieved.

[0210] In one embodiment, as Figure 15 shown, a network quality prediction device 1500 is provided, which is applied to an electronic device. The device includes:

[0211] The radio frequency fingerprint information acquisition module 1520 is configured to obtain the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period if the network quality prediction start condition is met;

[0212] The movement trajectory determination module 1540 is configured to determine the movement trajectory of the electronic device within a preset time period according to the radio frequency fingerprint information of each communication network;

[0213] The network quality prediction module 1560 is configured to perform quality prediction on the network to be connected by the electronic device within a prediction time period according to the movement trajectory and a preset network quality map, and generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the movement route and the network quality of the preset communication networks.

[0214] In one embodiment, the movement trajectory determination module 1540 is further configured to:

[0215] Match the radio frequency fingerprint information of each communication network with a preset radio frequency fingerprint map in sequence to determine the movement trajectory of the electronic device within a preset time period; the preset radio frequency fingerprint map is used to represent the radio frequency fingerprint information of the preset communication networks corresponding to each feature position on the movement route of the electronic device.

[0216] In one embodiment, as Figure 16 shown, the radio frequency fingerprint information includes a cell identifier and signal strength information; the movement trajectory determination module 1540 includes:

[0217] An acquisition unit 1542, configured to, for each communication network, acquire the cell identifier and signal strength information of the communication network from the radio frequency fingerprint information of the communication network;

[0218] A matching unit 1544, configured to match the cell identifier and signal strength information of the communication network with the cell identifier and signal strength information of the preset communication network in the preset radio frequency fingerprint map to determine the preset communication network matched with each communication network;

[0219] A movement trajectory generation unit 1546, configured to generate the movement trajectory of the electronic device within a preset time period based on the feature positions corresponding to each preset communication network.

[0220] In one embodiment, the matching unit 1544 is further configured to: match the cell identifier of the communication network with the preset cell identifiers in the preset radio frequency fingerprint map to determine the target cell identifier; the target cell identifier is the cell identifier with successful matching; for each target cell identifier, match the signal strength information corresponding to the cell identifier of the communication network with the preset signal strength information corresponding to the target cell identifier in the preset radio frequency fingerprint map to determine the target preset signal strength information; the target preset signal strength information is the preset signal strength information with successful matching; based on the target cell identifier and the target preset signal strength information, determine the preset communication network that matches each communication network.

[0221] In one embodiment, the motion trajectory generation unit 1546 is further configured to: obtain the characteristic positions corresponding to each preset communication network from the preset radio frequency fingerprint map, and generate a characteristic position sequence based on the characteristic positions corresponding to each preset communication network; determine whether the characteristic position sequence meets the preset position sequence condition; if the characteristic position sequence meets the preset position sequence condition, use the characteristic position sequence as the motion trajectory of the electronic device within the preset time period.

[0222] In one embodiment, the network quality prediction enabling condition includes that the application program currently running on the electronic device is a preset application program.

[0223] In one embodiment, the preset network quality map includes a first preset network quality map, and the first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running the preset application program on the moving route, the network quality parameters of the preset communication network, the preset application program, and the usage period; the network quality prediction module 1560 includes:

[0224] A motion state determination unit, configured to determine the motion state of the electronic device as a stationary state or a moving state according to the motion trajectory;

[0225] A first prediction result generation unit, configured to, if it is determined that the motion state of the electronic device is a stationary state, perform quality prediction on the network to be connected by the electronic device during the prediction time period according to the target characteristic positions in the motion trajectory in combination with the preset radio frequency fingerprint map and the first preset network quality map, and generate a first prediction result.

[0226] In one embodiment, the first prediction result generation unit is further configured to: obtain the network quality parameter of the current communication network connected to the electronic device; determine whether the network quality parameter of the current communication network is lower than a preset network quality threshold; if the network quality parameter of the current communication network is lower than the preset network quality threshold, then combine the target feature position in the movement trajectory with the preset radio frequency fingerprint map and the first preset network quality map to perform quality prediction on the network to be connected by the electronic device during the prediction time period, and generate a first prediction result.

[0227] In one embodiment, the first prediction result generation unit is further configured to: output a first prompt message, where the first prompt message is used to prompt that the electronic device has accessed a communication network with a network quality parameter lower than the preset network quality threshold; search in the preset radio frequency fingerprint map for a first candidate communication network set corresponding to the target feature position; search in the first preset network quality map for first candidate network quality parameters corresponding to the first candidate communication network set, the prediction time period, and the preset application program, and generate a first prediction result according to the first candidate network quality parameters.

[0228] In one embodiment, a network quality prediction device is provided, and further includes:

[0229] The first network switching module is configured to, if the first prediction result is that there is a first target communication network in the first candidate communication network set with a network quality parameter higher than or equal to the preset network quality threshold, then switch from the current communication network to the first target communication network.

[0230] In one embodiment, if the network quality prediction enabling condition includes that the application program currently running on the electronic device is a preset application program, then the preset network quality map includes a first preset network quality map. The first preset network quality map is used to represent the corresponding relationship between the preset communication network accessed by the electronic device when running the preset application program on the movement route, the network quality parameter of the preset communication network, the preset application program, and the usage period. A network quality prediction device is provided, and further includes:

[0231] The second prediction result generation unit is configured to, if it is determined that the movement state of the electronic device is a moving state, then obtain the current feature position in the movement trajectory and at least one predicted feature position along the forward direction of the movement trajectory; based on the current feature position and the at least one predicted feature position, combine the preset radio frequency fingerprint map and the first preset network quality map to perform quality prediction on the network to be connected by the electronic device during the prediction time period, and generate a second prediction result.

[0232] In one embodiment, the second prediction result generation unit is further configured to find a second candidate communication network set corresponding to the current feature position and at least one predicted feature position from a preset radio frequency fingerprint map; find second candidate network quality parameters corresponding to the second candidate communication network set, a predicted time period, and a preset application program from a first preset network quality map, and generate a second prediction result according to the second candidate network quality parameters.

[0233] In one embodiment, if the second candidate network quality parameters include a second candidate communication network in the second candidate communication network set whose network quality parameter is lower than a preset network quality threshold, a network quality prediction device is further provided, including:

[0234] A first network switching module, configured to output a second prompt message for prompting that the electronic device is about to access a communication network whose network quality parameter is lower than a preset network quality threshold; determine whether there is a second target communication network in the second candidate communication networks whose network quality parameter is higher than or equal to the preset network quality threshold; if there is a second target communication network, switch to the second target communication network when it is detected that the electronic device accesses a communication network whose network quality parameter is lower than the preset network quality threshold.

[0235] In one embodiment, a network quality prediction device is further provided, including:

[0236] A first preset network quality map generation module, configured to, for each preset application program, obtain a preset communication network, a usage period, and a network quality parameter of the preset communication network when the electronic device runs the preset application program on a moving route; generate a first preset network quality map based on the preset communication network, the usage period, and the network quality parameter of the preset communication network corresponding to each preset application program.

[0237] In one embodiment, the first target communication network and the second target communication network include a communication network based on the fifth-generation mobile communication technology 5G or a communication network based on the sixth-generation mobile communication technology 6G.

[0238] It should be understood that although the steps in the above flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0239] The division of each module in the above network quality prediction device is only for illustrative purposes. In other embodiments, the network quality prediction device can be divided into different modules as needed to complete all or part of the functions of the above network quality prediction device.

[0240] For the specific limitations of the network quality prediction device, reference can be made to the limitations of the network quality prediction method in the above text, which will not be elaborated here. Each module in the above network quality prediction device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0241] Figure 17 It is a schematic internal structure diagram of an electronic device in an embodiment. The electronic device can be any terminal device such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a PDA (Personal Digital Assistant), a POS (Point of Sales), a vehicle-mounted computer, a wearable device, etc. The electronic device includes a processor and a memory connected through a system bus. Among them, the processor can include one or more processing units. The processor can be a CPU (Central Processing Unit) or a DSP (Digital Signal Processing), etc. The memory can include a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The computer program can be executed by the processor to implement a network quality prediction method provided in each of the following embodiments. The internal memory provides a high-speed cache operating environment for the operating system computer program in the non-volatile storage medium.

[0242] In the embodiments of the present application, the implementation of each module in the provided network quality prediction device can be in the form of a computer program. The computer program can run on the electronic device. The program module formed by the computer program can be stored on the memory of the electronic device. When the computer program is executed by the processor, the steps of the method described in the embodiments of the present application are implemented.

[0243] The embodiments of the present application also provide a computer-readable storage medium. One or more non-volatile computer-readable storage media containing computer-executable instructions, when the computer-executable instructions are executed by one or more processors, cause the processors to execute the steps of the network quality prediction method.

[0244] An embodiment of the present application further provides a computer program product containing instructions. When it runs on a computer, it causes the computer to execute a network quality prediction method.

[0245] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties.

[0246] Any reference to memory, storage, database, or other media used in this application may include non-volatile and / or volatile memory. Non-volatile memory may include ROM (Read-Only Memory), PROM (Programmable Read-only Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-only Memory), or flash memory. Volatile memory may include RAM (Random Access Memory), which serves as an external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as SRAM (Static Random Access Memory), DRAM (Dynamic Random Access Memory), SDRAM (Synchronous Dynamic Random Access Memory), double data rate DDR SDRAM (Double Data Rate Synchronous Dynamic Random Access memory), ESDRAM (Enhanced Synchronous Dynamic Random Access memory), SLDRAM (Sync Link Dynamic Random Access Memory), RDRAM (Rambus Dynamic Random Access Memory), DRDRAM (Direct Rambus Dynamic Random Access Memory).

[0247] The above embodiments merely represent several implementation manners of this application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of this application. It should be noted that for those of ordinary skill in the art, without departing from the concept of this application, several modifications and improvements can still be made, and these all belong to the protection scope of this application. Therefore, the protection scope of the patent of this application shall be subject to the appended claims.

Claims

1. A network quality prediction method, characterized in that, Applied to an electronic device, the method includes: If a network quality prediction start condition is met, obtain the radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period; Determine the movement trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of each communication network; Perform quality prediction on the network to be connected by the electronic device during a prediction time period according to the movement trajectory and a preset network quality map, and generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on a movement route and the network quality of the preset communication networks; Wherein, the network quality prediction start condition includes that the application program currently running on the electronic device is a preset application program; the preset network quality map includes a first preset network quality map, and the first preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on a movement route when running the preset application program, the network quality parameters of the preset communication networks, and the preset application program and the usage period; The performing quality prediction on the network to be connected by the electronic device during a prediction time period according to the movement trajectory and a preset network quality map, and generating a prediction result includes: Determine the movement state of the electronic device as a stationary state or a moving state according to the movement trajectory; if it is determined that the movement state of the electronic device is a stationary state, perform quality prediction on the network to be connected by the electronic device during a prediction time period according to a target feature position in the movement trajectory, a preset radio frequency fingerprint map, and the first preset network quality map, and generate a first prediction result.

2. The method according to claim 1, wherein The determining the movement trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of each communication network includes: Match the radio frequency fingerprint information of each communication network with a preset radio frequency fingerprint map in sequence to determine the movement trajectory of the electronic device within the preset time period; the preset radio frequency fingerprint map is used to represent the radio frequency fingerprint information of the preset communication networks corresponding to each feature position on the movement route of the electronic device.

3. The method according to claim 2, wherein The radio frequency fingerprint information includes a cell identifier and signal strength information; the matching the radio frequency fingerprint information of each communication network with a preset radio frequency fingerprint map in sequence to determine the movement trajectory of the electronic device within the preset time period includes: For each communication network, obtain the cell identifier and signal strength information of the communication network from the radio frequency fingerprint information of the communication network; Match the cell identifier and signal strength information of the communication network with the cell identifier and signal strength information of the preset communication network in the preset radio frequency fingerprint map to determine the preset communication network matched with each communication network; Generate the movement trajectory of the electronic device within the preset time period based on the feature positions corresponding to each preset communication network.

4. The method according to claim 3, wherein Matching the cell identification and signal strength information of the communication network with the cell identification and signal strength information of the preset communication network in the preset radio frequency fingerprint map to determine the preset communication network matching each communication network, including: Matching the cell identification of the communication network with the preset cell identification in the preset radio frequency fingerprint map to determine the target cell identification; the target cell identification is the cell identification with successful matching; For each of the target cell identifications, matching the signal strength information corresponding to the cell identification of the communication network with the preset signal strength information corresponding to the target cell identification in the preset radio frequency fingerprint map to determine the target preset signal strength information; the target preset signal strength information is the preset signal strength information with successful matching; Based on the target cell identification and the target preset signal strength information, determine the preset communication network matching each communication network.

5. The method according to claim 3, wherein Generating the movement trajectory of the electronic device within the preset time period based on the characteristic positions corresponding to each preset communication network, including: Obtain the characteristic positions corresponding to each preset communication network from the preset radio frequency fingerprint map, and generate a characteristic position sequence based on the characteristic positions corresponding to each preset communication network; Determine whether the characteristic position sequence meets the preset position sequence condition; If the characteristic position sequence meets the preset position sequence condition, use the characteristic position sequence as the movement trajectory of the electronic device within the preset time period.

6. The method according to claim 1, characterized in that According to the target characteristic position in the movement trajectory, combining the preset radio frequency fingerprint map and the first preset network quality map, predicting the quality of the network to be connected by the electronic device during the prediction time period, and generating a first prediction result, including: Obtain the network quality parameters of the current communication network to which the electronic device is connected; Determine whether the network quality parameters of the current communication network are lower than the preset network quality threshold; If the network quality parameters of the current communication network are lower than the preset network quality threshold, then according to the target characteristic position in the movement trajectory, combining the preset radio frequency fingerprint map and the first preset network quality map, predict the quality of the network to be connected by the electronic device during the prediction time period, and generate a first prediction result.

7. The method according to claim 6, wherein According to the target characteristic position in the movement trajectory, combining the preset radio frequency fingerprint map and the first preset network quality map, predicting the quality of the network to be connected by the electronic device during the prediction time period, and generating a first prediction result, including: Output a first prompt message, where the first prompt message is used to prompt that the electronic device has accessed a communication network with network quality parameters lower than the preset network quality threshold; Search in the preset radio frequency fingerprint map for a first candidate communication network set corresponding to the target characteristic position; Search in the first preset network quality map for first candidate network quality parameters corresponding to the first candidate communication network set, the prediction time period, and the preset application program, and generate a first prediction result according to the first candidate network quality parameters.

8. The method according to claim 7, characterized in that The method further includes: If the first prediction result is that there is a first target communication network in the first candidate communication network set whose network quality parameter is higher than or equal to a preset network quality threshold, then switch from the current communication network to the first target communication network.

9. The method according to claim 1, characterized in that The method further includes: If it is determined that the motion state of the electronic device is a moving state, then obtain the current feature position in the motion trajectory and at least one predicted feature position along the forward direction of the motion trajectory; Based on the current feature position and the at least one predicted feature position, in combination with a preset radio frequency fingerprint map and the first preset network quality map, perform quality prediction on the network to be connected by the electronic device during a predicted time period, and generate a second prediction result.

10. The method according to claim 9, wherein The performing quality prediction on the network to be connected by the electronic device during a predicted time period, and generating a second prediction result based on the current feature position and the at least one predicted feature position, in combination with a preset radio frequency fingerprint map and the first preset network quality map, includes: Search in the preset radio frequency fingerprint map for a second candidate communication network set corresponding to the current feature position and the at least one predicted feature position; Search in the first preset network quality map for second candidate network quality parameters corresponding to the second candidate communication network set, the predicted time period, and the preset application program, and generate a second prediction result according to the second candidate network quality parameters.

11. The method according to claim 10, wherein If the second candidate network quality parameters include a second candidate communication network in the second candidate communication network set whose network quality parameter is lower than a preset network quality threshold, then the method further includes: Output a second prompt message, where the second prompt message is used to prompt that the electronic device is about to access a communication network whose network quality parameter is lower than a preset network quality threshold; Determine whether there is a second target communication network in the second candidate communication networks whose network quality parameter is higher than or equal to a preset network quality threshold; If there is the second target communication network, then when it is detected that the electronic device accesses a communication network whose network quality parameter is lower than a preset network quality threshold, switch to the second target communication network.

12. The method according to any one of claims 1 to 11, characterized in that, The method further includes: For each of the preset application programs, obtain the preset communication network connected by the electronic device when running the preset application program on the moving route, the usage period, and the network quality parameter of the preset communication network; Generate the first preset network quality map based on the preset communication network, the usage period, and the network quality parameter of the preset communication network corresponding to each of the preset application programs.

13. A network quality prediction device, characterized in that, Applied to an electronic device, the apparatus includes: A radio frequency fingerprint information acquisition module, configured to obtain radio frequency fingerprint information of each communication network connected to the electronic device within a preset time period if a network quality prediction start condition is met; A motion trajectory determination module, configured to determine the motion trajectory of the electronic device within the preset time period according to the radio frequency fingerprint information of each communication network; A network quality prediction module, configured to predict the quality of the network to be connected by the electronic device within a prediction time period according to the motion trajectory and a preset network quality map, and generate a prediction result; the preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the moving route and the network quality of the preset communication networks; Wherein, the network quality prediction enabling condition includes that the application currently running on the electronic device is a preset application; the preset network quality map includes a first preset network quality map, and the first preset network quality map is used to represent the corresponding relationship between the preset communication networks accessed by the electronic device on the moving route when running the preset application, the network quality parameters of the preset communication networks, the preset application, and the usage period; The network quality prediction module is configured to: determine the motion state of the electronic device as a stationary state or a moving state according to the motion trajectory; if it is determined that the motion state of the electronic device is a stationary state, then predict the quality of the network to be connected by the electronic device within a prediction time period according to the target feature position in the motion trajectory, in combination with a preset radio frequency fingerprint map and the first preset network quality map, and generate a first prediction result.

14. An electronic device, including a memory and a processor, wherein a computer program is stored in the memory, characterized in that, When the computer program is executed by the processor, the processor is caused to execute the steps of the network quality prediction method according to any one of claims 1 to 12.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the network quality prediction method according to any one of claims 1 to 12 are implemented.

16. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the network quality prediction method according to any one of claims 1 to 12 are implemented.

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