Base station-based resource processing method, device and equipment

Abstract

The present application provides a method, device and equipment for resource processing based on a base station, which relates to communication technology. The method includes: when a fault is detected in a first base station, determining the idle resources of a second base station corresponding to the first base station, and the time when the fault occurs; wherein the first base station and the second base station are different types of provider equipment; based on a preset service prediction model and the time when the fault occurs, predicting the service volume of the first base station at the next moment; wherein the service prediction model is obtained by training according to services at different moments; and according to the service volume of the first base station at the next moment, allocating the idle resources of the second base station to the access users of the first base station. The method of the present application realizes the allocation of idle resources to the access users of the first base station in a targeted manner through a base station of a different network according to the service volume of the first base station that changes at every moment, thereby solving the technical problem of low utilization of base station resources.

Description

Technical Field

[0001] The present application relates to communication technology, and in particular to a method, device and equipment for resource processing based on a base station. Background Art

[0002] At present, with the rapid development of wireless communication technology, the number of access users such as 4 / 5G is also increasing rapidly, and base stations need to provide wireless networks to more access users.

[0003] In the prior art, when a base station provides a wireless network to an access user, the base stations of different operators are usually forcibly merged to obtain merged base station resources, and then the merged base station resources are allocated to the access users in the corresponding area.

[0004] However, in the prior art, since the number of access users in the area changes dynamically, while the merged base station resources are fixed values, when the merged base station resources are allocated to the access users, the base station cannot dynamically load all the access users, resulting in low utilization of the base station resources. Summary of the invention

[0005] The present application provides a base station-based resource processing method, device and equipment to solve the technical problem of low utilization rate of base station resources.

[0006] In a first aspect, the present application provides a base station-based resource processing method, which is applied to an electronic device, and the method includes:

[0007] When a failure of a first base station is detected, determining idle resources of a second base station corresponding to the first base station and a time when the failure occurs; wherein the first base station and the second base station are different types of provider equipment;

[0008] Based on a preset service prediction model and the time when the fault occurs, predict the service volume of the first base station at the next time; wherein the service prediction model is obtained by training according to services at different times;

[0009] According to the traffic volume of the first base station at the next moment, idle resources of the second base station are allocated to access users of the first base station.

[0010] Further, when it is detected that the first base station has a fault, determining idle resources of a second base station corresponding to the first base station and a time when the fault occurs includes:

[0011] When it is detected that the first base station has a fault, determining the time when the fault of the first base station occurs, and determining a second base station located in the same area as the first base station according to a correspondence between the first base station, the second base station, and the area;

[0012] Determine idle resources of the second base station.

[0013] Further, determining the idle resources of the second base station includes:

[0014] Determine the idle resources of the second base station according to an average value of the traffic of the second base station within a preset time range, a preset weight, and a maximum available resource of the second base station;

[0015] Among them, the idle resources of the second base station are w=P-(A+A*B); wherein P is the maximum available resources of the second base station, A is the average value of the service volume of the second base station within a preset time range, and B is the preset weight.

[0016] Further, allocating idle resources of the second base station to access users of the first base station according to the traffic volume of the first base station at the next moment includes:

[0017] Determine the number of first access users corresponding to the traffic of the first base station at the next moment, and the number of second access users corresponding to the idle resources;

[0018] If it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment, determining the number of second access users corresponding to the idle resources as the number of first users to be allocated at the next moment;

[0019] Allocating idle resources of the second base station to access users of the first base station according to the first number of users to be allocated at the next moment;

[0020] If it is determined that the idle resources of the second base station are greater than or equal to the traffic volume of the first base station at the next moment, determining the first access user number as the second user number to be allocated at the next moment;

[0021] According to the second number of users to be allocated at the next moment, idle resources of the second base station are allocated to the access users of the first base station.

[0022] Furthermore, the method further comprises:

[0023] Acquire internal parameters of the first base station, and predict the traffic volume of the first base station at the current moment according to a preset traffic prediction model;

[0024] Based on the internal parameters and the traffic volume at the current moment, determining the operating state of the first base station at the current moment through preset base station information;

[0025] When the operating state of the first base station at the current moment is abnormal, it is determined that a fault occurs in the first base station.

[0026] Furthermore, the method further comprises:

[0027] Obtain the number of users accessing the base station at different times;

[0028] Determine the time interval in which the number of access users at each moment falls within a plurality of preset time intervals;

[0029] Count the traffic volume corresponding to the number of access users in each time interval;

[0030] The initial time training model is trained according to the time interval and the traffic volume corresponding to the number of access users in each time interval until the time series model converges to obtain a traffic prediction model.

[0031] In a second aspect, the present application provides a base station-based resource processing device, which is applied to an electronic device, and the device includes:

[0032] A first determining unit is configured to determine, when a failure of a first base station is detected, idle resources of a second base station corresponding to the first base station and a time when the failure occurs; wherein the first base station and the second base station are different types of provider equipment;

[0033] A first prediction unit, configured to predict the traffic volume of the first base station at the next moment based on a preset traffic prediction model and the time when the fault occurs; wherein the traffic prediction model is obtained by training according to traffic at different moments;

[0034] An allocation unit is used to allocate idle resources of the second base station to access users of the first base station according to the traffic volume of the first base station at the next moment.

[0035] Furthermore, the first determining unit includes:

[0036] a first determining module, configured to determine a time when a fault of the first base station occurs when a fault of the first base station is detected, and determine a second base station located in the same area as the first base station according to a correspondence between the first base station, the second base station, and the area;

[0037] The second determining module is used to determine the idle resources of the second base station.

[0038] Furthermore, the second determining module is specifically configured to:

[0039] Determine the idle resources of the second base station according to an average value of the traffic of the second base station within a preset time range, a preset weight, and a maximum available resource of the second base station;

[0040] Among them, the idle resources of the second base station are w=P-(A+A*B); wherein P is the maximum available resources of the second base station, A is the average value of the service volume of the second base station within a preset time range, and B is the preset weight.

[0041] Furthermore, the allocation unit comprises:

[0042] A third determination module is used to determine the number of first access users corresponding to the service volume of the first base station at the next moment, and the number of second access users corresponding to the idle resources;

[0043] a fourth determination module, configured to determine, if it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment, the number of second access users corresponding to the idle resources as the number of first users to be allocated at the next moment;

[0044] A first allocation module, configured to allocate idle resources of the second base station to access users of the first base station according to the first number of users to be allocated at the next moment;

[0045] a fifth determining module, configured to determine the first number of access users as the second number of users to be allocated at the next moment if it is determined that the idle resources of the second base station are greater than or equal to the traffic volume of the first base station at the next moment;

[0046] The second allocation module is used to allocate the idle resources of the second base station to the access users of the first base station according to the number of second users to be allocated at the next moment.

[0047] Furthermore, the device also includes:

[0048] A second prediction unit, configured to obtain internal parameters of the first base station, and predict the traffic volume of the first base station at a current moment according to a preset traffic prediction model;

[0049] A determination unit, configured to determine the operation state of the first base station at the current moment through preset base station information based on the internal parameters and the traffic volume at the current moment;

[0050] The second determining unit is configured to determine that a fault occurs in the first base station when the operating state of the first base station at a current moment is abnormal.

[0051] Furthermore, the device also includes:

[0052] An acquisition unit, used to acquire the number of access users of the base station at different times;

[0053] A third determining unit, configured to determine, among a plurality of preset time intervals, a time interval in which the number of access users at each moment is located;

[0054] A statistical unit, used to count the traffic volume corresponding to the number of access users in each time interval;

[0055] The training unit is used to train the initial time training model according to the time interval and the business volume corresponding to the number of access users in each time interval until the time series model converges to obtain a business prediction model.

[0056] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0057] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in the first aspect.

[0058] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the method described in the first aspect when executed by a processor.

[0059] The present application provides a method, device and equipment for resource processing based on a base station. When a fault is detected in the first base station, the idle resources of the second base station corresponding to the first base station and the time when the fault occurs are determined; wherein the first base station and the second base station are different types of provider equipment; based on a preset business prediction model and the time when the fault occurs, the business volume of the first base station at the next moment is predicted; wherein the business prediction model is obtained by training according to the business at different moments; according to the business volume of the first base station at the next moment, the idle resources of the second base station are allocated to the access users of the first base station. In this scheme, when a fault is detected in the first base station, the idle resources of the second base station corresponding to the first base station and the time when the fault occurs are determined, and then the business volume of the first base station at the next moment is predicted based on the preset business prediction model and the time when the fault occurs, and finally, based on the load capacity of the idle resources, the idle resources of the second base station are allocated to the access users of the first base station according to the business volume of the first base station at the next moment. Therefore, according to the business volume of the first base station at the next moment predicted by the business prediction model, the idle resources of the second base station are allocated to the access users of the first base station, thereby realizing the targeted allocation of idle resources to the access users of the first base station through the base stations of the foreign network according to the business volume that changes at all times of the first base station, thereby avoiding the phenomenon that idle resources still exist in the base stations of the foreign network when the first base station is under high resource load or resource shortage, and solving the technical problem of low utilization rate of base station resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0061] Figure 1 A schematic diagram of a flow chart of a base station-based resource processing method provided in an embodiment of the present application;

[0062] Figure 2 A schematic diagram of a flow chart of another base station-based resource processing method provided in an embodiment of the present application;

[0063] Figure 3 A schematic diagram of the structure of a resource processing device based on a base station provided in an embodiment of the present application;

[0064] Figure 4 A schematic diagram of the structure of another base station-based resource processing device provided in an embodiment of the present application;

[0065] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0066] Figure 6 A block diagram of an electronic device provided in an embodiment of the present application.

[0067] The above drawings show clear embodiments of the present disclosure, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0068] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present disclosure.

[0069] In one example, with the rapid development of wireless communication technology, the number of 4 / 5G and other access users is also increasing rapidly, and base stations need to provide wireless networks to more access users. In the prior art, when a base station provides a wireless network to an access user, it usually forcibly merges base stations of different operators to obtain merged base station resources, and then allocates the merged base station resources to the access users in the corresponding area. However, in the prior art, since the number of access users in a region changes dynamically, and the merged base station resources are fixed values, when allocating the merged base station resources to the access users, the base station cannot dynamically load all access users, which leads to low utilization of base station resources.

[0070] The present application provides a base station-based resource processing method, device and equipment, which aim to solve the above technical problems in the prior art.

[0071] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0072] Figure 1 A flow chart of a method for resource processing based on a base station provided in an embodiment of the present application is applied to electronic devices, such as Figure 1 As shown, the method includes:

[0073] 101. When a failure of a first base station is detected, determine idle resources of a second base station corresponding to the first base station and a time when the failure occurs; wherein the first base station and the second base station are provider devices of different types.

[0074] For example, the execution subject of this embodiment may be an electronic device, or a terminal device, or a resource processing device or device based on a base station, or other devices or equipment that can execute this embodiment, and there is no limitation on this. This embodiment is introduced with the execution subject being an electronic device.

[0075] First, it is necessary to detect the operation status of the first base station. When it is detected that the first base station has a fault, the time when the fault of the first base station occurs is determined, and according to the correspondence between the first base station, the second base station and the area, the second base station located in the same area as the first base station is determined. Then, an acquisition request is sent to the second base station. The acquisition request is used to determine the resource status of the second base station. After the second base station receives the acquisition request, the second base station determines whether it can bear the access users of the first base station on the basis of ensuring the resources used for its own normal operation. If it can bear the access users of the first base station, the idle resources of the second base station are determined. Finally, the idle resources are sent to the electronic device, and the electronic device obtains the idle resources of the second base station.

[0076] Among them, the first base station and the second base station are different types of provider equipment, the coverage areas of the first base station and the second base station are basically the same, and when the first base station and the second base station are operating normally, the first base station and the second base station each provide resources for access users in the area.

[0077] 102. Based on a preset service prediction model and the time when the fault occurs, predict the service volume of the first base station at the next time; wherein the service prediction model is obtained by training according to services at different times.

[0078] Exemplarily, each moment is in a different time interval, and the business at each moment is also in a different time interval. Therefore, the business volume of the base station in different time intervals is used as sample data, and the final business prediction model is obtained through multiple trainings. The time series model is a supervisory algorithm generally applicable in the current machine learning field. For example, the time series model can be: Long Short-Term Memory (LSTM), Auto-Regressive and Moving Average Model (ARMA) and other algorithm models. Among them, the business volume is the total voice business volume and data business volume of the base station in a certain time interval, and can further include the maximum number of access users, total Internet traffic, and call traffic volume under the base station in a certain time interval.

[0079] For example, the business volume of the base station at different times can be predicted based on the business prediction model. When the time when the fault occurs in the first base station is obtained, the time when the fault occurs is input into the business prediction model, and the business volume of the first base station at the next time can be predicted based on the business prediction model.

[0080] 103. Allocate idle resources of the second base station to access users of the first base station according to the traffic volume of the first base station at the next moment.

[0081] Exemplarily, when the electronic device obtains the traffic volume of the first base station at the next moment, it first determines the load capacity of the idle resources of the second base station. If the idle resources can bear the entire traffic volume at the next moment, the access terminal of all access users of the first base station can be changed to the second base station, and the idle resources of the second base station are allocated to all access users of the first base station according to the traffic volume of the first base station at the next moment. Alternatively, if the idle resources cannot bear the entire traffic volume at the next moment, the access terminal of some access users of the first base station can be changed to the second base station, and the idle resources of the second base station are allocated to some access users of the first base station according to the traffic volume of the first base station at the next moment. At this time, the second base station bears part of the traffic volume at the next moment. If the second base station has no idle resources, no resource allocation is performed.

[0082] For example, the traffic volume of the first base station at the next moment is 100 access users, the total Internet traffic a corresponding to the 100 access users, and the call traffic volume b. Therefore, if the idle resources can bear the total Internet traffic a and call traffic volume b corresponding to the 100 access users at the next moment, the access terminal of the 100 access users of the first base station can be changed to the second base station, and the idle resources of the second base station can be allocated to all the access users of the first base station according to the traffic volume of the first base station at the next moment. Alternatively, if the idle resources cannot bear the total Internet traffic a and call traffic volume b corresponding to the 100 access users at the next moment, it is necessary to determine the number of access users that the idle resources can bear. For example, according to the total Internet traffic a and call traffic volume b corresponding to the 100 access users, and the idle resources, it is determined that the number of access users that the idle resources can bear is 50 people. Then the access terminal of the 50 access users of the first base station can be changed to the second base station, and according to the traffic volume of the first base station at the next moment, the idle resources of the second base station can be allocated to the 50 access users of the first base station. Alternatively, if the idle resources cannot bear the total Internet traffic a and call traffic b corresponding to the 100 access users at the next moment, no resource allocation is performed.

[0083] In an embodiment of the present application, when a fault is detected in the first base station, the idle resources of the second base station corresponding to the first base station and the time when the fault occurs are determined; wherein the first base station and the second base station are different types of provider equipment. Based on a preset business prediction model and the time when the fault occurs, the business volume of the first base station at the next moment is predicted; wherein the business prediction model is obtained by training according to the business at different moments. According to the business volume of the first base station at the next moment, the idle resources of the second base station are allocated to the access users of the first base station. In this scheme, when a fault is detected in the first base station, the idle resources of the second base station corresponding to the first base station and the time when the fault occurs are determined, and then based on the preset business prediction model and the time when the fault occurs, the business volume of the first base station at the next moment is predicted, and finally based on the load capacity of the idle resources, according to the business volume of the first base station at the next moment, the idle resources of the second base station are allocated to the access users of the first base station. Therefore, according to the business volume of the first base station at the next moment predicted by the business prediction model, the idle resources of the second base station are allocated to the access users of the first base station, thereby realizing the targeted allocation of idle resources to the access users of the first base station through the base stations of the foreign network according to the business volume that changes at all times of the first base station, thereby avoiding the phenomenon that idle resources still exist in the base stations of the foreign network when the first base station is under high resource load or resource shortage, and solving the technical problem of low utilization rate of base station resources.

[0084] Figure 2 A flow chart of another base station-based resource processing method provided in an embodiment of the present application is as follows: Figure 2 As shown, the method includes:

[0085] 201. Obtain the number of users accessing the base station at different times.

[0086] Exemplarily, the electronic device can obtain the access user terminals of the base station at different times, and each access user terminal represents an access user. Therefore, the number of access users of the base station at different times can be determined according to the number of access user terminals, where the access user terminals include: mobile terminals, Internet of Things terminals, etc.

[0087] 202. Determine, among a plurality of preset time intervals, a time interval in which the number of access users at each moment lies.

[0088] Exemplarily, the electronic device can pre-set multiple time intervals, and then judge each moment, determine the time interval at each moment, and then determine the time interval at which the number of access users at each moment is located. Therefore, in each time interval, there are multiple numbers of access users, and then the business volume in each time interval can be determined. Among them, the time interval is a pre-set data collection interval, and it can also be a time interval determined by calculation based on data sampling points. The time unit of the time interval can be a conventional time unit such as seconds and minutes. For example, the base station sampling data interval is 60 seconds, and the corresponding time interval is 60 seconds; similarly, the second data sampling minus the first data sampling time, the final result is the time interval.

[0089] 203. Count the business volume corresponding to the number of access users in each time interval.

[0090] Exemplarily, the traffic includes voice traffic data and data traffic data, etc. The electronic device can count the voice traffic data and data traffic data corresponding to the number of connected users in each time interval, and determine the proportion of voice traffic data and the proportion of data traffic data in the traffic volume.

[0091] 204. According to the time interval and the service volume corresponding to the number of access users in each time interval, the initial time training model is trained until the time series model converges to obtain a service prediction model.

[0092] Exemplarily, the electronic device may train the initial time training model according to the time interval and the voice service data and data service data corresponding to the number of access users in each time interval, and obtain the service prediction model when the time series model converges.

[0093] 205. Obtain internal parameters of the first base station, and predict the traffic volume of the first base station at the current moment according to a preset traffic prediction model.

[0094] Exemplarily, the internal parameters include the license standard, bandwidth and other parameters of the first base station. The electronic device can obtain the license standard, bandwidth and other parameters of the first base station, and then input the current moment into a preset business prediction model to predict the business volume of the first base station at the current moment. Among them, the license standards include GNU General Public License (GPL), GNU Lesser General Public License (LGPL), BSD License, MIT License, Mozilla Public License 1.1 (MPL), Common Development and Distribution License (CDDL), Apache License, etc.

[0095] 206. Based on the internal parameters and the current traffic volume, determine the operating status of the first base station at the current moment through preset base station information.

[0096] Exemplarily, the preset base station information is the abnormal judgment standard for the existing network 2G, 3G, 4G, 5G, and the planned network 6G. It should be noted that for base stations with different parameter types, the upper limit of the corresponding business volume is also different, and the upper limit of the corresponding business volume of base stations with different network standards is also different. At the same time, the abnormal standards of base stations with different network standards and different parameter types are also different, and specific reference needs to be made to the actual existing network standards of different operators. The electronic device can determine the base station information corresponding to the current business volume based on internal parameters and the current business volume, and then judge the operating status of the first base station at the current moment based on the base station information, where the operating status includes base station failure, base station high load, base station interference and other base station phenomena that affect user voice and Internet perception.

[0097] For example, based on internal parameters and the current business volume, the electronic device determines that the base station information corresponding to the current business volume is the abnormal judgment standard under the 2G condition, and then judges the operating status of the first base station at the current moment according to the 2G abnormal judgment standard.

[0098] 207. When the operating state of the first base station at the current moment is abnormal, determine that a fault occurs in the first base station.

[0099] Exemplarily, when the operating status of the first base station at the current moment is base station high load, the electronic device determines that the first base station has a fault; or, when the operating status of the first base station at the current moment is base station fault, the electronic device determines that the first base station has a fault; or, when the operating status of the first base station at the current moment is base station interference, the electronic device determines that the first base station has a fault.

[0100] 208. When a failure of the first base station is detected, determine the time when the failure of the first base station occurs, and determine a second base station located in the same area as the first base station based on the correspondence between the first base station, the second base station, and the area; wherein the first base station and the second base station are provider devices of different types.

[0101] Exemplarily, when a fault is detected in the first base station, the electronic device can determine the time when the fault occurs in the first base station, and determine the second base station located in the same area as the first base station according to the correspondence between the first base station, the second base station, and the area. The first base station and the second base station are different types of provider equipment, and the coverage areas of the first base station and the second base station are substantially overlapped.

[0102] 209. Determine idle resources of the second base station.

[0103] In one example, the idle resources of the second base station are determined based on the average value of the business volume of the second base station within a preset time range, a preset weight, and the maximum available resources of the second base station; wherein the idle resources of the second base station are w=P-(A+A*B); wherein P is the maximum available resources of the second base station, A is the average value of the business volume of the second base station within the preset time range, and B is the preset weight.

[0104] Exemplarily, the electronic device first determines the maximum available resources of the second base station, and then determines the idle resources of the second base station based on the average value of the business volume of the second base station within a preset time range and a preset weight. The idle resources of the second base station are w=P-(A+A*B), wherein P is the maximum available resources of the second base station, A is the average value of the business volume of the second base station within the preset time range, the business volume may refer to the number of accessed users and the business usage resources of the accessed users, and B is the preset weight. Through A+A*B, the second base station increases a certain amount of floating on the basis of the average value, thereby ensuring the resources required for the second base station to operate correctly. When P-(A+A*B), the idle resources of the second base station can be obtained.

[0105] 210. Based on a preset service prediction model and the time when the fault occurs, predict the service volume of the first base station at the next time; wherein the service prediction model is obtained by training according to services at different times.

[0106] For example, this step can be referred to Figure 1 Step 102 in the above is not described in detail.

[0107] 211. Determine the number of first access users corresponding to the traffic of the first base station at the next moment and the number of second access users corresponding to the idle resources.

[0108] Exemplarily, the electronic device may determine the number of first access users corresponding to the traffic at the next moment and the number of second access users corresponding to the idle resources according to the traffic of the first base station at the next moment.

[0109] 212. If it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment, determine the number of second access users corresponding to the idle resources as the first number of users to be allocated at the next moment.

[0110] Exemplarily, the electronic device first compares the idle resources of the second base station with the business volume of the first base station at the next moment to determine the load capacity of the idle resources of the second base station. If the idle resources are less than the total business volume of the first base station at the next moment, the number of second access users corresponding to the idle resources is determined to be the first number of users to be allocated at the next moment. At this time, the idle resources can bear part of the business volume of the first base station at the next moment, that is, bear part of the access users of the first base station at the next moment.

[0111] 213. Allocate idle resources of the second base station to access users of the first base station according to the first number of users to be allocated at the next moment.

[0112] Exemplarily, the electronic device may change the access terminal of some access users of the first base station to the second base station at the next moment according to the number of first users to be allocated at the next moment, and allocate the idle resources of the second base station to some access users of the first base station according to the traffic volume of the first base station at the next moment.

[0113] 214. If it is determined that the idle resources of the second base station are greater than or equal to the service volume of the first base station at the next moment, determine the number of first access users as the number of second users to be allocated at the next moment.

[0114] Exemplarily, if the idle resources are greater than or equal to the traffic volume of the first base station at the next moment, it means that the idle resources can bear the entire traffic volume of the first base station at the next moment, and then the number of first access users is determined to be the second number of users to be allocated at the next moment. At this time, the idle resources can bear the entire traffic volume of the first base station at the next moment, that is, bear all access users of the first base station at the next moment.

[0115] 215. Allocate idle resources of the second base station to access users of the first base station according to the number of second users to be allocated at the next moment.

[0116] Exemplarily, the electronic device can change the access terminal of all access users of the first base station to the second base station at the next moment according to the number of second users to be allocated at the next moment, and allocate the idle resources of the second base station to all access users of the first base station according to the business volume of the first base station at the next moment.

[0117] In an embodiment of the present application, the number of access users of a base station at different times is obtained. In a plurality of preset time intervals, the time interval in which the number of access users at each time is located is determined. The traffic volume corresponding to the number of access users in each time interval is counted. According to the time interval and the traffic volume corresponding to the number of access users in each time interval, the initial time training model is trained until the time series model converges to obtain a traffic prediction model. The internal parameters of the first base station are obtained, and the traffic volume of the first base station at the current time is predicted according to the preset traffic prediction model. Based on the internal parameters and the traffic volume at the current time, the operation state of the first base station at the current time is determined by the preset base station information. When the operation state of the first base station at the current time is abnormal, it is determined that the first base station has a fault. When a fault is detected in the first base station, the time when the fault of the first base station occurs is determined, and according to the correspondence between the first base station, the second base station, and the region, the second base station located in the same region as the first base station is determined; wherein the first base station and the second base station are different types of provider equipment. The idle resources of the second base station are determined. Based on the preset traffic prediction model and the time when the fault occurs, the traffic volume of the first base station at the next time is predicted; wherein the traffic prediction model is obtained by training according to the traffic at different times. Determine the number of first access users corresponding to the traffic volume of the first base station at the next moment, and the number of second access users corresponding to the idle resources. If it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment, determine the number of second access users corresponding to the idle resources as the first number of users to be allocated at the next moment. According to the first number of users to be allocated at the next moment, allocate the idle resources of the second base station to the access users of the first base station. If it is determined that the idle resources of the second base station are greater than or equal to the traffic volume of the first base station at the next moment, determine the number of first access users as the second number of users to be allocated at the next moment. According to the second number of users to be allocated at the next moment, allocate the idle resources of the second base station to the access users of the first base station. Therefore, according to the traffic volume of the first base station at the next moment predicted by the traffic prediction model, the idle resources of the second base station are allocated to the access users of the first base station, so that the idle resources are allocated to the access users of the first base station in a targeted manner through the base station of the other network according to the traffic volume of the first base station that changes at the moment, and avoid the phenomenon that the base station of the other network still has idle resources when the first base station is under high resource load and resource shortage, and solve the technical problem of low utilization rate of base station resources.

[0118] Figure 3A schematic diagram of a resource processing device based on a base station provided in an embodiment of the present application is applied to electronic devices, such as Figure 3 As shown, the device comprises:

[0119] The first determining unit 31 is used to determine the idle resources of the second base station corresponding to the first base station and the time when the failure occurs when a failure is detected in the first base station; wherein the first base station and the second base station are different types of provider equipment.

[0120] The first prediction unit 32 is used to predict the service volume of the first base station at the next moment based on a preset service prediction model and the time when the fault occurs; wherein the service prediction model is obtained by training according to services at different moments.

[0121] The allocation unit 33 is configured to allocate idle resources of the second base station to access users of the first base station according to the traffic volume of the first base station at the next moment.

[0122] The device of this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principles are the same and will not be repeated here.

[0123] Figure 4 A schematic diagram of another base station-based resource processing device provided in an embodiment of the present application, Figure 3 Based on the embodiment shown, Figure 4 As shown, the first determining unit 31 includes:

[0124] The first determination module 311 is used to determine the time when the first base station fails when a failure is detected, and determine the second base station located in the same area as the first base station according to the correspondence between the first base station, the second base station and the area.

[0125] The second determining module 312 is configured to determine idle resources of the second base station.

[0126] In one example, the second determining module 312 is specifically configured to:

[0127] The idle resources of the second base station are determined based on the average value of the business volume of the second base station within a preset time range, the preset weight, and the maximum available resources of the second base station; wherein the idle resources of the second base station are w=P-(A+A*B); wherein P is the maximum available resources of the second base station, A is the average value of the business volume of the second base station within the preset time range, and B is the preset weight.

[0128] In one example, the allocation unit 33 includes:

[0129] The third determination module 331 is used to determine the number of first access users corresponding to the service volume of the first base station at the next moment and the number of second access users corresponding to the idle resources.

[0130] The fourth determining module 332 is configured to determine the second number of access users corresponding to the idle resources as the first number of users to be allocated at the next moment if it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment.

[0131] The first allocation module 333 is configured to allocate idle resources of the second base station to access users of the first base station according to the first number of users to be allocated at a next moment.

[0132] The fifth determining module 334 is configured to determine the first number of access users as the second number of users to be allocated at the next moment if it is determined that the idle resources of the second base station are greater than or equal to the traffic volume of the first base station at the next moment.

[0133] The second allocation module 335 is configured to allocate idle resources of the second base station to access users of the first base station according to the number of second users to be allocated at a next moment.

[0134] In one example, the device further includes:

[0135] The second prediction unit 41 is used to obtain internal parameters of the first base station and predict the traffic volume of the first base station at the current moment according to a preset traffic prediction model.

[0136] The judgment unit 42 is used to judge the operation status of the first base station at the current moment based on the internal parameters and the traffic volume at the current moment through preset base station information.

[0137] The second determining unit 43 is configured to determine that a fault occurs in the first base station when the operating state of the first base station at the current moment is abnormal.

[0138] In one example, the device further includes:

[0139] The acquisition unit 44 is used to acquire the number of users accessing the base station at different times.

[0140] The third determining unit 45 is configured to determine the time interval in which the number of access users at each moment falls among a plurality of preset time intervals.

[0141] The statistical unit 46 is used to count the traffic volume corresponding to the number of access users in each time interval.

[0142] The training unit 47 is used to train the initial time training model according to the time interval and the business volume corresponding to the number of access users in each time interval until the time series model converges to obtain a business prediction model.

[0143] The device of this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principles are the same and will not be repeated here.

[0144] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the electronic device includes: a memory 51 and a processor 52.

[0145] The memory 51 stores a computer program that can be executed on the processor 52 .

[0146] The processor 52 is configured to execute the method provided in the above embodiment.

[0147] The electronic device further includes a receiver 53 and a transmitter 54. The receiver 53 is used to receive instructions and data sent by an external device, and the transmitter 54 is used to send instructions and data to the external device.

[0148] Figure 6 This is a block diagram of an electronic device provided in an embodiment of the present application. The electronic device may be a mobile phone, a computer, a digital broadcast terminal, a message transceiver, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0149] The device 600 may include one or more of the following components: a processing component 602 , a memory 604 , a power component 606 , a multimedia component 608 , an audio component 610 , an input / output (I / O) interface 612 , a sensor component 614 , and a communication component 616 .

[0150] The processing component 602 generally controls the overall operation of the device 600, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 602 may include one or more modules to facilitate the interaction between the processing component 602 and other components. For example, the processing component 602 may include a multimedia module to facilitate the interaction between the multimedia component 608 and the processing component 602.

[0151] The memory 604 is configured to store various types of data to support operations on the device 600. Examples of such data include instructions for any application or method operating on the device 600, contact data, phone book data, messages, pictures, videos, etc. The memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0152] The power supply component 606 provides power to the various components of the device 600. The power supply component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 600.

[0153] The multimedia component 608 includes a screen that provides an output interface between the device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0154] The audio component 610 is configured to output and / or input audio signals. For example, the audio component 610 includes a microphone (MIC), and when the device 600 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 604 or sent via the communication component 616. In some embodiments, the audio component 610 also includes a speaker for outputting audio signals.

[0155] I / O interface 612 provides an interface between processing component 602 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0156] The sensor assembly 614 includes one or more sensors for providing various aspects of status assessment for the device 600. For example, the sensor assembly 614 can detect the open / closed state of the device 600, the relative positioning of components, such as the display and keypad of the device 600, the sensor assembly 614 can also detect the position change of the device 600 or a component of the device 600, the presence or absence of user contact with the device 600, the orientation or acceleration / deceleration of the device 600 and the temperature change of the device 600. The sensor assembly 614 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 614 can also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 can also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor or a temperature sensor.

[0157] The communication component 616 is configured to facilitate wired or wireless communication between the device 600 and other devices. The device 600 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 616 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0158] In an exemplary embodiment, the apparatus 600 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0159] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions, and the instructions can be executed by the processor 620 of the device 600 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0160] An embodiment of the present application also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the method provided by the above embodiment.

[0161] An embodiment of the present application also provides a computer program product, which includes: a computer program, which is stored in a readable storage medium, and at least one processor of an electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device executes the solution provided by any of the above embodiments.

[0162] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0163] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A resource processing method based on a base station, characterized in that: Applied to electronic equipment, the method comprises: Acquire internal parameters of the first base station, and predict the traffic volume of the first base station at the current moment according to a preset traffic prediction model; Based on the internal parameters and the traffic volume at the current moment, determining the operating state of the first base station at the current moment through preset base station information; When the operating state of the first base station at the current moment is abnormal, determining that the first base station has a fault; When a failure of the first base station is detected, determining idle resources of a second base station corresponding to the first base station and a time when the failure occurs; wherein the first base station and the second base station are different types of provider equipment; Based on the service prediction model and the time when the fault occurs, predict the service volume of the first base station at the next time; wherein the service prediction model is obtained by training according to services at different times; Determine the number of first access users corresponding to the traffic of the first base station at the next moment, and the number of second access users corresponding to the idle resources; If it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment, determining the number of second access users corresponding to the idle resources as the number of first users to be allocated at the next moment; Allocating idle resources of the second base station to access users of the first base station according to the first number of users to be allocated at the next moment; If it is determined that the idle resources of the second base station are greater than or equal to the traffic volume of the first base station at the next moment, determining the first access user number as the second user number to be allocated at the next moment; According to the second number of users to be allocated at the next moment, idle resources of the second base station are allocated to the access users of the first base station.

2. The method according to claim 1, characterized in that When it is detected that the first base station fails, determining idle resources of a second base station corresponding to the first base station and a time when the failure occurs includes: When it is detected that the first base station has a fault, determining the time when the fault of the first base station occurs, and determining a second base station located in the same area as the first base station according to a correspondence between the first base station, the second base station, and the area; Determine idle resources of the second base station.

3. The method according to claim 2, characterized in that Determining idle resources of the second base station includes: Determine the idle resources of the second base station according to an average value of the traffic of the second base station within a preset time range, a preset weight, and a maximum available resource of the second base station; Among them, the idle resources of the second base station are w=P-(A+A*B); wherein P is the maximum available resources of the second base station, A is the average value of the service volume of the second base station within a preset time range, and B is the preset weight.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: Obtain the number of users accessing the base station at different times; Determine the time interval in which the number of access users at each moment falls within a plurality of preset time intervals; Count the traffic volume corresponding to the number of access users in each time interval; The initial time training model is trained according to the time interval and the traffic volume corresponding to the number of access users in each time interval until the time series model converges to obtain a traffic prediction model.

5. A resource processing device based on a base station, characterized in that: Applied to electronic equipment, the device comprises: A first determining unit is configured to determine, when a failure of a first base station is detected, idle resources of a second base station corresponding to the first base station and a time when the failure occurs; wherein the first base station and the second base station are different types of provider equipment; A first prediction unit, configured to predict the traffic volume of the first base station at the next moment based on a preset traffic prediction model and the time when the fault occurs; wherein the traffic prediction model is obtained by training according to traffic at different moments; An allocation unit, used to determine the number of first access users corresponding to the traffic volume of the first base station at the next moment, and the number of second access users corresponding to the idle resources; if it is determined that the idle resources of the second base station are less than the traffic volume of the first base station at the next moment, then determine the number of second access users corresponding to the idle resources as the first number of users to be allocated at the next moment; according to the first number of users to be allocated at the next moment, allocate the idle resources of the second base station to the access users of the first base station; if it is determined that the idle resources of the second base station are greater than or equal to the traffic volume of the first base station at the next moment, then determine the first number of access users as the second number of users to be allocated at the next moment; according to the second number of users to be allocated at the next moment, allocate the idle resources of the second base station to the access users of the first base station; The device also includes: A second prediction unit, configured to obtain internal parameters of the first base station, and predict the traffic volume of the first base station at a current moment according to a preset traffic prediction model; A determination unit, configured to determine the operation state of the first base station at the current moment through preset base station information based on the internal parameters and the traffic volume at the current moment; The second determining unit is configured to determine that a fault occurs in the first base station when the operating state of the first base station at a current moment is abnormal.

6. The device according to claim 5, characterized in that The first determining unit includes: a first determining module, configured to determine a time when a fault of the first base station occurs when a fault of the first base station is detected, and determine a second base station located in the same area as the first base station according to a correspondence between the first base station, the second base station, and the area; The second determining module is used to determine the idle resources of the second base station.

7. The device according to claim 6, characterized in that The second determining module is specifically used to: Determine the idle resources of the second base station according to an average value of the traffic of the second base station within a preset time range, a preset weight, and a maximum available resource of the second base station; Among them, the idle resources of the second base station are w=P-(A+A*B); wherein P is the maximum available resources of the second base station, A is the average value of the service volume of the second base station within a preset time range, and B is the preset weight.

8. The device according to any one of claims 5 to 7, characterized in that: The device also includes: An acquisition unit, used to acquire the number of access users of the base station at different times; A third determining unit, configured to determine, among a plurality of preset time intervals, a time interval in which the number of access users at each moment lies; A statistical unit, used to count the traffic volume corresponding to the number of access users in each time interval; The training unit is used to train the initial time training model according to the time interval and the business volume corresponding to the number of access users in each time interval until the time series model converges to obtain a business prediction model.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method according to any one of claims 1 to 4 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 4 when executed by a processor.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 4 when being executed by a processor.

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