Base station wakeup method, device, equipment, medium and program product

Abstract

The invention provides a base station awakening method and device, equipment, a medium and a program product. The method comprises the following steps: firstly, when a target base station is in a dormant state, for each target grid, determining a first MR sampling total number of all base stations corresponding to the target grid within a first preset duration; then, if it is determined that the first MR sampling total number is larger than the preset MR sampling number, the wake-up index of the target grid is obtained; then, adding the wake-up indexes of all the target grids, and determining a target wake-up index corresponding to the target base station; and finally, if the target wake-up index is greater than the preset wake-up index, waking up the target base station. According to the method provided by the invention, the surrounding flow change condition can be dynamically adapted, the high-quality network service is provided for the user in time, and the user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a base station wake-up method, device, equipment, medium and program product. Background Art

[0002] As mobile network technology continues to develop, network base stations continue to increase network energy consumption while providing high-quality services. Deep sleep is an energy-saving technology widely used in wireless communication equipment. By powering off most of the components of the active antenna unit (AAU) and remote radio unit (RRU), only retaining the basic connection with the baseband unit (BBU), energy consumption can be greatly reduced. However, how to flexibly wake up the base station after deep sleep to ensure the user experience is an urgent problem to be solved.

[0003] In the prior art, for base stations in deep sleep, the only way to ensure network coverage of surrounding areas within a specific period of time is to set a scheduled wake-up, thereby ensuring that users can conduct normal business. For example, suppose a base station is located near a large stadium. Since the stadium does not hold events on weekdays, there is less network traffic around it, so the base station is usually in deep sleep to save energy. However, when there are events or activities at the stadium, a large number of users will gather around the venue, and network demand will increase dramatically. To meet this demand, the base station can be scheduled to wake up a few hours before the game to ensure that users can be provided with sufficient network coverage and stable communication services during the event.

[0004] However, the existing base station wake-up method cannot dynamically respond to network traffic fluctuations, and thus cannot provide users with high-quality network services in a timely manner, reducing user experience. Summary of the invention

[0005] The present application provides a base station wake-up method, device, equipment, medium and program product to solve the technical problem that the prior art cannot dynamically respond to network traffic fluctuations, thereby failing to provide users with high-quality network services in a timely manner and reducing user experience.

[0006] In a first aspect, the present application provides a base station wake-up method, comprising:

[0007] When the target base station is in a dormant state, for each target grid, determining the total number of first MR samples of all base stations corresponding to the target grid within a first preset time period, wherein the target grid is a grid in which the serving base station is the target base station when the target base station is in a non-dormant state;

[0008] If it is determined that the first MR sampling total number is greater than the preset MR sampling number, obtaining a wake-up index of the target grid, where the wake-up index is proportional to the degree to which the target base station needs to be woken up;

[0009] Adding the wake-up indexes of all target grids to determine a target wake-up index corresponding to the target base station;

[0010] If the target wake-up index is greater than the preset wake-up index, the target base station is woken up.

[0011] Optionally, for each target grid, determining the total number of first MR samplings of all base stations corresponding to the target grid within a first preset time period includes:

[0012] Within the first preset time period, collecting first MR data of all base stations according to a preset MR sampling period;

[0013] Performing rasterization processing on the MR data of the base station to generate a plurality of grids;

[0014] For each target grid among the multiple grids, the first MR sampling number of each base station corresponding to the target grid is summed to determine the total number of first MR samplings of the target grid.

[0015] Optionally, when the target base station is in a non-sleep state, the method further includes:

[0016] For each target grid, determining a second MR sampling number and RSRP of each base station corresponding to the target grid within a second preset time length;

[0017] The wake-up index of the target grid is determined according to the second MR sampling number and RSRP of each base station corresponding to the target grid.

[0018] Optionally, determining the wake-up index of the target grid according to the second MR sampling number and RSRP of each base station corresponding to the target grid includes:

[0019] Determining the type of the target grid according to the RSRP of each base station corresponding to the target grid;

[0020] The wake-up index of the target grid is determined according to the type of the target grid and the corresponding second MR sampling number of each base station.

[0021] Optionally, determining the wake-up index of the target grid according to the type of the target grid and the corresponding second MR sampling number of each base station includes:

[0022] Determine the total number of second MR samples of all base stations corresponding to the target grid according to the second MR sample number of each base station corresponding to the target grid;

[0023] For each type, summing up the total number of second MR samplings of the target grid corresponding to the type to obtain the total number of third MR samplings;

[0024] For each target grid, the awakening index of the target grid is determined according to the total number of second MR samplings and the total number of third MR samplings corresponding to the target grid and a preset weight corresponding to the type of the target grid.

[0025] Optionally, determining the type of the target grid according to the RSRP of each base station corresponding to the target grid includes:

[0026] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and the RSRPs of all neighboring base stations are lower than the preset RSRP, determining that the target grid is of the first type;

[0027] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and there is a neighboring base station whose RSRP is not lower than the preset RSRP, determining that the target grid is of the second type;

[0028] If the RSRP of the target base station in the target grid is less than the preset RSRP, and there is a neighboring base station whose RSRP is not less than the preset RSRP, determining that the target grid is of the third type;

[0029] The base stations corresponding to the target grid include the target base station and at least one neighboring base station.

[0030] Optionally, for each target grid, determining the second MR sampling number and RSRP of each base station corresponding to the target grid within a second preset time period includes:

[0031] Within the second preset time period, collecting second MR data of all base stations according to the preset MR sampling period;

[0032] Performing rasterization processing on the second MR data of all base stations to generate a plurality of grids;

[0033] For each target grid among the multiple grids, the second MR sampling number and RSRP of each base station corresponding to the target grid are determined according to the second MR data of each base station corresponding to the target grid.

[0034] Optionally, the method further comprises:

[0035] The preset MR sampling number is determined according to the first preset time length and the MR sampling period.

[0036] In a second aspect, the present application provides a base station wake-up device, including:

[0037] A first determination module is used to determine, for each target grid, a total number of first MR samples of all base stations corresponding to the target grid within a first preset time period when the target base station is in a dormant state, wherein the target grid is a grid in which the serving base station is the target base station when the target base station is in a non-dormant state;

[0038] An acquisition module, configured to acquire a wake-up index of the target grid if it is determined that the first MR sampling total number is greater than a preset MR sampling number, wherein the wake-up index is proportional to the degree to which the target base station needs to be awakened;

[0039] A second determination module is used to sum the wake-up indexes of all target grids to determine a target wake-up index corresponding to the target base station;

[0040] The wake-up module is used to wake up the target base station if the target wake-up index is greater than a preset wake-up index.

[0041] Optionally, the first determining module is specifically configured to:

[0042] Within the first preset time period, collecting first MR data of all base stations according to a preset MR sampling period;

[0043] Performing rasterization processing on the MR data of the base station to generate a plurality of grids;

[0044] For each target grid among the multiple grids, the first MR sampling number of each base station corresponding to the target grid is summed to determine the total number of first MR samplings of the target grid.

[0045] Optionally, the third determining module is used to:

[0046] For each target grid, determining a second MR sampling number and RSRP of each base station corresponding to the target grid within a second preset time length;

[0047] The wake-up index of the target grid is determined according to the second MR sampling number and RSRP of each base station corresponding to the target grid.

[0048] Optionally, the third determining module is specifically configured to:

[0049] Determining the type of the target grid according to the RSRP of each base station corresponding to the target grid;

[0050] The wake-up index of the target grid is determined according to the type of the target grid and the corresponding second MR sampling number of each base station.

[0051] Optionally, the third determining module is specifically configured to:

[0052] Determine the total number of second MR samples of all base stations corresponding to the target grid according to the second MR sample number of each base station corresponding to the target grid;

[0053] For each type, summing up the total number of second MR samplings of the target grids corresponding to the type to obtain the total number of third MR samplings;

[0054] For each target grid, the awakening index of the target grid is determined according to the total number of second MR samplings and the total number of third MR samplings corresponding to the target grid and a preset weight corresponding to the type of the target grid.

[0055] Optionally, the third determining module is specifically configured to:

[0056] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and the RSRPs of all neighboring base stations are lower than the preset RSRP, determining that the target grid is of the first type;

[0057] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and there is a neighboring base station whose RSRP is not lower than the preset RSRP, determining that the target grid is of the second type;

[0058] If the RSRP of the target base station in the target grid is less than the preset RSRP, and there is a neighboring base station whose RSRP is not less than the preset RSRP, determining that the target grid is of the third type;

[0059] The base stations corresponding to the target grid include the target base station and at least one neighboring base station.

[0060] Optionally, the third determining module is specifically configured to:

[0061] Within the second preset time period, collecting second MR data of all base stations according to the preset MR sampling period;

[0062] Performing rasterization processing on the second MR data of all base stations to generate a plurality of grids;

[0063] For each target grid among the multiple grids, the second MR sampling number and RSRP of each base station corresponding to the target grid are determined according to the second MR data of each base station corresponding to the target grid.

[0064] Optionally, the acquisition module is further used to:

[0065] The preset MR sampling number is determined according to the first preset time length and the MR sampling period.

[0066] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0067] Memory stores computer-executable instructions;

[0068] The processor executes the computer-executable instructions stored in the memory to implement the base station wake-up method as described in the above-mentioned first aspect and various possible implementation methods of the first aspect.

[0069] In a fourth aspect, the present application provides a computer-readable storage medium, comprising computer execution instructions. When a processor executes the computer execution instructions, the base station wake-up method as described in the above-mentioned first aspect and various possible implementation methods of the first aspect is executed.

[0070] In a fifth aspect, the present application provides a program product, which includes a computer program, and the computer program is executed by a processor to implement the base station wake-up method as described in the first aspect and various possible implementation methods of the first aspect.

[0071] The base station wake-up method, device, equipment, medium and program product provided by the present application are as follows: first, when the target base station is in a dormant state, for each target grid, the total number of first MR samples of all base stations corresponding to the target grid is counted within a first preset time period to obtain the traffic status of the target grid, so as to adjust the operating status of the base station in time; then, if the determined total number of first MR samples exceeds the preset MR sample number, indicating that there is a significant traffic fluctuation in the grid, it is necessary to obtain the wake-up index of the target grid, and then obtain the wake-up index of all target grids with significant traffic fluctuations, and sum these wake-up indexes to determine the target wake-up index corresponding to the target base station; finally, if the target wake-up index is greater than the preset wake-up index, the target base station is awakened, avoiding unnecessary awakening of the target base station. Through this method, the base station can dynamically adjust the state of the base station according to the actual traffic demand around it, reduce network energy consumption, reduce the decline in network performance, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0073] Figure 1 A system diagram of a base station wake-up method provided in an embodiment of the present application;

[0074] Figure 2 Schematic diagram of the process of the base station wake-up method provided in the embodiment of the present application Figure 1 ;

[0075] Figure 3 The process flow of the base station wake-up method provided in the embodiment of the present application Figure 2 ;

[0076] Figure 4 A schematic diagram of the structure of a base station wake-up device provided in an embodiment of the present application;

[0077] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0078] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0079] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0080] 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 used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0081] As mobile network technology continues to develop, network base stations continue to increase network energy consumption while providing high-quality services. Deep sleep is an energy-saving technology widely used in wireless communication equipment. By powering off most of the components of AAU and RRU and only retaining the basic connection with BBU, energy consumption can be greatly reduced. However, how to flexibly wake up the base station after deep sleep to ensure the user experience is an urgent problem to be solved.

[0082] In the prior art, for base stations in deep sleep, the only way to ensure network coverage of surrounding areas within a specific period of time is to set a scheduled wake-up, thereby ensuring that users can conduct normal business. For example, suppose a base station is located near a large stadium. Since the stadium does not hold events on weekdays, there is less network traffic around it, so the base station is usually in deep sleep to save energy. However, when there are events or activities at the stadium, a large number of users will gather around the venue, and network demand will increase dramatically. To meet this demand, the base station can be scheduled to wake up a few hours before the game to ensure that users can be provided with sufficient network coverage and stable communication services during the event.

[0083] However, the existing base station wake-up method cannot dynamically respond to network traffic fluctuations and can only be used in the early morning or in some special scenarios. For sudden situations, such as emergencies, a large number of users gather near the target dormant base station, generating a large traffic demand. However, since the target base station can only be awakened at a scheduled time, it is impossible to provide users with high-quality network services in a timely manner, reducing the user experience.

[0084] Based on this, the present application proposes a base station wake-up method, device, equipment, medium and program product. Since the target base station cannot obtain the traffic demand of different surrounding areas when it is in sleep mode, the base station can only be awakened in a timed manner. However, since the network coverage of the base station is wide and there will be overlap, the non-sleeping base station adjacent to the target base station can be used to obtain the total number of first measurement report (MeasurementReport, MR) samples of different areas (i.e., target grids) around the target base station to determine whether it is necessary to wake up the target base station, that is, first determine the first MR sampling number of all base stations corresponding to each area around the target base station, and then, if the first MR sampling number determined in the area is greater than the preset MR sampling number, it indicates that there is a certain traffic fluctuation in the area, and then obtain the demand degree for waking up the target base station in the area (i.e., the wake-up index). Similarly, the demand degree of all awakening target base stations is obtained and summed to determine the target demand degree corresponding to the target base station. Finally, if the target demand index exceeds the preset threshold, the target base station is awakened. In this way, the base station can dynamically adjust its status according to the actual traffic demand in the surrounding area, thereby reducing network energy consumption while providing users with high-quality network services, reducing the decline in network performance, ensuring users' network needs, and improving user experience.

[0085] 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.

[0086] Figure 1 A system diagram of a base station wake-up method provided in an embodiment of the present application; Figure 1 As shown, it includes: an operation and maintenance center, a target base station, and base stations A, B, and C adjacent to the target base station.

[0087] The Operation and Maintenance Center (OMC) is an important part of the communication network, which is used to monitor, manage and maintain the operating status of network equipment. OMC coordinates the normal operation of multiple devices and base stations in the network through a centralized control system to ensure the reliability and efficiency of the network. OMC is usually interconnected with base stations, switching centers, transmission systems and other equipment in the telecommunications network to realize remote management and maintenance functions.

[0088] The target base station is a dormant base station; base station A, base station B, and base station C are base stations that are located near the target base station and are not dormant.

[0089] When the target base station is dormant, the OMC obtains the total number of first MR samplings of base stations A, B, and C corresponding to each grid of the target base station, and when the total number of first MR samplings of the target grid is greater than the preset MR sampling number, the OMC obtains the wake-up index of the target grid. Finally, it determines whether to wake up the target base station based on the sum of the wake-up indexes of all the target grids obtained.

[0090] Figure 2 Schematic diagram of the process of the base station wake-up method provided in the embodiment of the present application Figure 1 ;like Figure 2 As shown, the method includes:

[0091] S201 : When a target base station is in a dormant state, for each target grid, determine the total number of first MR samples of all base stations corresponding to the target grid within a first preset time period.

[0092] Among them, the target grid is the grid in which the serving base station is the target base station when the target base station is in a non-sleep state; a time window pre-set for the first preset time length; the total number of MR sampling is the number of MR data collected by all base stations corresponding to the target grid within the first preset time length, which is used to indicate the activity of the user; the MR data is the signal receiving power sent by the user terminal to the base station.

[0093] It is understandable that when the target base station is in a dormant state, in order to obtain the network demand of users in the target grid, all base stations corresponding to the target grid (i.e., neighboring base stations of the target base station) can be used to determine the total number of first MR samplings of all base stations corresponding to the target grid within the first preset time length, so as to further determine whether there are many users in the target grid. This achieves that even if the target base station is in a dormant state, the target grid can still be dynamically monitored.

[0094] In an achievable manner, a specific method for determining the total number of first MR samples of all base stations corresponding to the target grid is:

[0095] First, within a first preset time length, the first MR data of all base stations are collected according to a preset MR sampling period; secondly, the MR data of the base stations are rasterized to generate multiple grids; finally, for each target grid in the multiple grids, the first MR sampling number of each base station corresponding to the target grid is summed up to determine the total number of first MR sampling of the target grid.

[0096] It can be understood that the first MR data of all base stations collected are rasterized, that is, the first MR data of all base stations are mapped to the corresponding grid according to the geographical location (such as longitude and latitude), and the first MR data are associated with the corresponding grid to finally generate multiple grids, so as to more finely analyze the user activity in the grid and dynamically monitor the grid; then the number of samples of the first MR data of each base station corresponding to the grid is summed to obtain the total number of first MR samples of the target grid to reflect the user activity of the target grid within the first preset time length, as well as the network demand status.

[0097] For example, within the first preset time length, the first MR data of all base stations are collected according to the preset MR sampling period as shown in Table 1, and then after the rasterization process, one of the target grids formed may be as shown in Table 2.

[0098] Table 1 First MR data table

[0099]

[0100] Table 2 Target grid MR sampling table

[0101] longitude latitude The total number of first MR samples 116.23231 39.41341 125

[0102] S202: If it is determined that the first MR sampling total number is greater than the preset MR sampling number, then obtaining a wake-up index of the target grid.

[0103] Among them, the awakening index can be used to measure the comprehensive index of user demand and signal quality in the target grid. The awakening index is proportional to the degree to which the target base station needs to be awakened, that is, the higher the awakening index, the higher the necessity for the target base station to be awakened.

[0104] It can be understood that when it is determined that the total number of first MR samples corresponding to the target grid is greater than the preset MR sampling number, it means that the user activity in the grid is relatively high, the user equipment interacts with the base station more frequently, and stronger network service support may be required. In this case, the wake-up index of the target grid is obtained as the basis for the final judgment on whether the base station needs to be woken up.

[0105] It should be noted that the preset MR sampling number is determined according to the first preset time length and the MR sampling period.

[0106] Specifically, the calculation formula of the preset MR sampling number can be expressed as:

[0107]

[0108] Among them, 15*60 is the first preset duration converted into seconds. α is a coefficient factor, and its value is [0, 1]. When α is 1, it means that during the sampling period, at least one user continues to do business in the target grid.

[0109] For example, assuming that α=0.5 and the MR sampling period is 5s, then according to the preset MR sampling number calculation formula, m can be obtained as 90. Assuming that the total number of the first MR samples of the target grid obtained through step S201 is 100, it means that the activity of users in the grid is relatively high, and further network service support can be provided to the grid, that is, the target grid is a valid grid.

[0110] S203: Add up the wake-up indexes of all target grids to determine a target wake-up index corresponding to the target base station.

[0111] It is understandable that this method uses multiple mechanisms to determine whether the target base station needs to be awakened, that is, first determine the target grids whose total number of first MR sampling is greater than the preset MR sampling number, then obtain the awakening indexes of these target grids respectively, and finally add up the awakening indexes of all target grids to determine the target awakening index corresponding to the target base station. This method avoids the target base station from being mistakenly awakened when the user demand is not high, reduces the frequent switching of base stations, and further reduces energy consumption.

[0112] S204: If the target wake-up index is greater than the preset wake-up index, the target base station is woken up.

[0113] Among them, the preset wake-up index avoids the situation where the base station is frequently woken up due to short-term traffic fluctuations, while ensuring timely response to network needs during peak demand, thereby achieving dual optimization of energy saving and network performance.

[0114] It should be noted that, in order to ensure the quality of network service in the target grid, the preset wake-up index is usually set to a value lower than 10.

[0115] It can be understood that when the target wake-up index is greater than the preset wake-up index, it means that the network services currently provided within the range of multiple or one target grid no longer meet the network requirements and more network service support is required. Therefore, the target base station needs to be woken up to ensure the user's network needs and improve the user experience.

[0116] The present application provides a base station wake-up method, by first, when the target base station is in a dormant state, for each target grid, within a first preset time length, counting the total number of first MR samples of all base stations corresponding to the target grid, so as to obtain the traffic status of the target grid, so as to timely adjust the operating status of the base station; then, if the determined total number of first MR samples exceeds the preset MR sample number, indicating that there is a significant traffic fluctuation in the grid, it is necessary to obtain the wake-up index of the target grid, and then obtain the wake-up index of all target grids with significant traffic fluctuations, and sum these wake-up indexes to determine the target wake-up index corresponding to the target base station; finally, if the target wake-up index is greater than the preset wake-up index, the target base station is awakened, avoiding unnecessary awakening of the target base station. Through this method, the base station can dynamically adjust the state of the base station according to the actual traffic demand around it, reduce network energy consumption, reduce the decline in network performance, and improve user experience.

[0117] Figure 3 The process flow of the base station wake-up method provided in the embodiment of the present application Figure 2 ;like Figure 3 As shown, this embodiment specifically describes how to determine the wake-up index of the target grid when the target base station is in a non-sleep state. The method includes:

[0118] S301 . For each target grid, determine a second MR sampling number and RSRP of each base station corresponding to the target grid within a second preset time period.

[0119] The reference signal receiving power (RSRP) is the average power of the base station reference signal received by the user equipment, reflecting the signal strength. The higher the RSRP value, the stronger the signal.

[0120] It is understandable that when the target base station is in a non-sleep state, in order to obtain accurate information about user activity and signal quality in different grids, it is necessary to perform MR sampling on each base station in the target grid within the second preset time length to determine the second MR sampling number and RSRP of each base station corresponding to the target grid. This provides a data basis for the subsequent determination of the wake-up index of the target grid.

[0121] In one achievable manner, the specific process of determining the second MR sampling number and RSRP of each base station corresponding to the target grid includes:

[0122] First, within a second preset time length, the second MR data of all base stations are collected according to a preset MR sampling period; secondly, the second MR data of all base stations are rasterized to generate a plurality of grids; finally, for each target grid in the plurality of grids, the second MR sampling number and RSRP of each base station corresponding to the target grid are determined according to the second MR data of each base station corresponding to the target grid.

[0123] For example, within the second preset time length, the second MR data of all base stations are collected according to the preset MR sampling period as shown in Table 3. Then, after rasterization processing, one of the target grids formed (taking grid (116.23231, 39.41341) as an example) can be shown in Table 4.

[0124] Table 3 Second MR data table

[0125]

[0126] Table 4 Target grid MR data table

[0127] longitude latitude Base station number Base station RSRP Base station sampling quantity 116.23231 39.41341 X -105 342 116.23231 39.41341 Y1 -113 10 116.23231 39.41341 Y2 -115 23 116.23231 39.41341 Y3 -11 1 51

[0128] It can be understood that the second MR data of all base stations collected are rasterized, that is, the second MR data of all base stations are mapped to the corresponding grids according to the underground position (such as longitude and latitude), and the second MR data are associated with the corresponding grids to finally generate multiple grids. The rasterized data can better provide a reference for the signal power adjustment of the base station, which is convenient for discovering user needs and signal coverage problems in a specific area; then the second MR data of each base station corresponding to the target grid is further processed to determine the second MR sampling number and RSRP of each base station corresponding to the target grid to reflect the user activity and network signal strength of the target grid within the second preset time length.

[0129] S302: Determine a wake-up index of the target grid according to the second MR sampling number and RSRP of each base station corresponding to the target grid.

[0130] It can be understood that since the wake-up index is a comprehensive indicator for measuring user demand and signal quality within the target grid, the size of the wake-up index is closely related to the second MR sampling number and RSRP of each base station corresponding to the grid. Therefore, by calculating the wake-up index based on the second MR sampling number and RSRP, the user demand and signal quality within the target grid can be accurately analyzed.

[0131] In one achievable manner, the specific process of determining the wake-up index of the target grid according to the second MR sampling number and RSRP of each base station corresponding to the target grid is:

[0132] First, the type of the target grid is determined according to the RSRP of each base station corresponding to the target grid; then, the wake-up index of the target grid is determined according to the type of the target grid and the corresponding second MR sampling number of each base station.

[0133] It can be understood that by classifying the target grids according to the RSRP of each base station corresponding to the target grid, the degree of demand for base station resources of different grids can be determined, and further combined with the second MR sampling number of each base station corresponding to the target grid, that is, the user activity in the target grid, the awakening index of the target grid can be finally determined.

[0134] It should be noted that the type of the target grid can be determined into three types according to the RSRP of the target base station and the RSRP of the neighboring base station, specifically including:

[0135] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and the RSRPs of all neighboring base stations are lower than the preset RSRP, the target grid is determined to be of the first type;

[0136] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and there is a neighboring base station whose RSRP is not lower than the preset RSRP, the target grid is determined to be the second type;

[0137] If the RSRP of the target base station in the target grid is less than the preset RSRP, and there is a neighboring base station whose RSRP is not less than the preset RSRP, the target grid is determined to be the third type;

[0138] The base stations corresponding to the target grid include the target base station and at least one neighboring base station. The neighboring base station refers to a base station that is geographically close to the target base station and has a certain overlap in network coverage area with the target base station.

[0139] Taking Table 4 in S301 as an example, assuming that base station X is the target base station, base stations Y1, Y2, and Y3 are neighboring base stations, and the preset RSRP is -110dBm, the target grid corresponding to Table 4 is the first type, that is, the RSRP of the target base station is not lower than the preset RSRP (-105dBm>-110dBm), and the RSRP of all neighboring base stations is less than the preset RSRP (-110dBm<-110dBm).

[0140] It can be understood that according to the size of the RSRP of the target base station and the RSRP of the neighboring base station, the grid is determined into three types, wherein the first type can be represented as the target base station in the grid has strong signal reception power and good network coverage, while the neighboring base station has weak signal reception power and poor network coverage, so the target base station needs to undertake the main network services in the target grid; the second type can be represented as the target base station and the neighboring base station in the grid have strong signal reception power and good network coverage, and the target base station and the neighboring base station can each undertake the network services in the target grid; the third type can be represented as the target base station in the grid has weak signal reception power and poor network coverage, while the neighboring base station has strong signal reception power and good network coverage, so the neighboring base station needs to undertake the main network services in the target grid. This classification method can provide an effective judgment basis for the wake-up of the target base station in the future.

[0141] In one achievable method, when determining the arousal index of the target grid, it is also necessary to use the total number of different MR samples of the target grid and the preset weight corresponding to the type of the target grid. The specific process is as follows:

[0142] First, the total number of second MR samplings of all base stations corresponding to the target grid is determined according to the number of second MR samplings of each base station corresponding to the target grid; secondly, for each type, the total number of second MR samplings of the target grid corresponding to the type is added to obtain the total number of third MR samplings; finally, for each target grid, the awakening index of the target grid is determined according to the total number of second MR samplings, the total number of third MR samplings and the preset weight corresponding to the type of the target grid.

[0143] The preset weight corresponding to the type of target grid is the weight set for different types of target grids according to actual needs.

[0144] For example, the preset weight of the first type of target grid may be set to 70, the preset weight of the second type of target grid may be set to 20, and the preset weight of the third type of target grid may be set to 10.

[0145] Specifically, taking the first type of target grid as an example, the calculation formula for the awakening index of each target grid in the first type of target grid is:

[0146]

[0147] Among them, A i is the second MR sampling number of the i-th target grid in the target grid of the first type, A all is the total number of third MR samples of the target grid belonging to the first type.

[0148] Furthermore, the calculation formula of the third MR sampling total number can be expressed as:

[0149]

[0150] Among them, A i is the second MR sampling number of the i-th target grid belonging to the first type of grid.

[0151] For example, assuming that the first type of target grid includes two target grids a and b, and the preset weight of the first type of target grid is 70, the total number of second MR samples in target grid a is 65, and the total number of second MR samples in target grid b is 35, then the total number of third MR samples of the first type of target grid is 100, the awakening index of target grid a in the first type of target grid is 45.5, and the awakening index of target grid b is 24.5. By analogy, the awakening index of each target grid in the second type and the third type of target grid can be calculated.

[0152] Optionally, after calculating the wake-up index of each target grid in each type of target grid, in order to more intuitively search for the wake-up index, a fingerprint code table of the target base station may be established.

[0153] It can be understood that by combining the total number of MR sampling, grid type and preset weight to calculate the wake-up index of each target grid in different types of target grids, it is possible to more accurately determine whether the target base station needs to be woken up, achieve accurate allocation of network resources, avoid over-reliance on a single base station, improve the stability of the entire network while reducing unnecessary energy consumption.

[0154] Figure 4 This is a schematic diagram of the structure of the base station wake-up device provided in the embodiment of the present application. Figure 4 As shown, the base station awakening device includes: a first determining module 401 , an acquiring module 402 , a second determining module 403 and an awakening module 404 .

[0155] A first determination module 401 is used to determine, for each target grid, a total number of first MR samples of all base stations corresponding to the target grid within a first preset time period when the target base station is in a dormant state, wherein the target grid is a grid in which the serving base station is the target base station when the target base station is in a non-dormant state;

[0156] The acquisition module 402 is used to acquire the wake-up index of the target grid if it is determined that the first MR sampling total number is greater than the preset MR sampling number, and the wake-up index is proportional to the degree to which the target base station needs to be awakened;

[0157] The second determination module 403 is used to sum the wake-up indexes of all target grids to determine the target wake-up index corresponding to the target base station;

[0158] The wake-up module 404 is configured to wake up the target base station if the target wake-up index is greater than a preset wake-up index.

[0159] Optionally, the first determining module 401 is specifically configured to:

[0160] Within a first preset time period, collecting first MR data of all base stations according to a preset MR sampling period;

[0161] rasterizing the MR data of the base station to generate a plurality of grids;

[0162] For each target grid among the multiple grids, the first MR sampling number of each base station corresponding to the target grid is summed up to determine the total number of first MR samplings of the target grid.

[0163] Optionally, the first determining module 401 is further configured to:

[0164] For each target grid, determining a second MR sampling number and RSRP of each base station corresponding to the target grid within a second preset time length;

[0165] The wake-up index of the target grid is determined according to the second MR sampling number and RSRP of each base station corresponding to the target grid.

[0166] Optionally, the device further includes a third determining module 405, specifically configured to:

[0167] Determine the type of the target grid according to the RSRP of each base station corresponding to the target grid;

[0168] The wake-up index of the target grid is determined according to the type of the target grid and the corresponding second MR sampling number of each base station.

[0169] Optionally, the third determining module 405 is specifically configured to:

[0170] Determine the total number of second MR samples of all base stations corresponding to the target grid according to the second MR sample number of each base station corresponding to the target grid;

[0171] For each type, the total number of second MR samples of the target grid corresponding to the type is summed to obtain the total number of third MR samples;

[0172] For each target grid, the awakening index of the target grid is determined according to the total number of second MR samplings and the total number of third MR samplings corresponding to the target grid and a preset weight corresponding to the type of the target grid.

[0173] Optionally, the third determining module 405 is specifically configured to:

[0174] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and the RSRPs of all neighboring base stations are lower than the preset RSRP, the target grid is determined to be of the first type;

[0175] If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and there is a neighboring base station whose RSRP is not lower than the preset RSRP, the target grid is determined to be the second type;

[0176] If the RSRP of the target base station in the target grid is less than the preset RSRP, and there is a neighboring base station whose RSRP is not less than the preset RSRP, the target grid is determined to be the third type;

[0177] The base stations corresponding to the target grid include the target base station and at least one neighboring base station.

[0178] Optionally, the third determining module 405 is specifically configured to:

[0179] Within a second preset time period, collecting second MR data of all base stations according to a preset MR sampling period;

[0180] Performing rasterization processing on the second MR data of all base stations to generate a plurality of grids;

[0181] For each target grid among the multiple grids, the second MR sampling number and RSRP of each base station corresponding to the target grid are determined according to the second MR data of each base station corresponding to the target grid.

[0182] Optionally, the acquisition module 402 is further configured to:

[0183] The preset MR sampling number is determined according to the first preset time length and the MR sampling period.

[0184] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown, the electronic device 50 provided in the embodiment of the present application includes: at least one processor 501 and a memory 502. The electronic device 50 also includes a communication component 503. The processor 501, the memory 502 and the communication component 503 are connected via a bus 504.

[0185] In a specific implementation process, at least one processor 501 executes the computer execution instructions stored in the memory 502, so that the at least one processor 501 executes the above-mentioned base station wake-up method.

[0186] The specific implementation process of the processor 501 can be found in the above-mentioned method embodiment, and its implementation principle and technical effect are similar, so the embodiments of the present application will not be repeated here.

[0187] The electronic device provided in the embodiment of the present application is used to execute the base station wake-up method provided in any of the above method embodiments. Its implementation principle and technical effect are similar and will not be repeated here.

[0188] In the above Figure 5 In the illustrated embodiment, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present application may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0189] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0190] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0191] The present application also provides a computer program product, including a computer program, which implements the above-mentioned base station wake-up method when executed by a processor.

[0192] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above-mentioned base station wake-up method is implemented.

[0193] The above-mentioned readable storage medium 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. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0194] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0195] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0196] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0197] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0198] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially or in other words, the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0199] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0200] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description 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 portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0201] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0202] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0203] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. If not specifically stated, the processor may be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, an ASIC, etc. If not specifically stated, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc.

[0204] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0205] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0206] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0207] It should be understood that the present application is not limited to the precise 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 application is limited only by the appended claims.

Claims

1. A base station wake-up method, characterized in that: include: When the target base station is in a dormant state, for each target grid, determining the total number of first measurement report MR samples of all base stations corresponding to the target grid within a first preset time length, wherein the target grid is a grid in which the serving base station is the target base station when the target base station is in a non-dormant state; If it is determined that the first MR sampling total number is greater than the preset MR sampling number, obtaining a wake-up index of the target grid, where the wake-up index is proportional to the degree to which the target base station needs to be woken up; Adding the wake-up indexes of all target grids to determine a target wake-up index corresponding to the target base station; If the target wake-up index is greater than the preset wake-up index, the target base station is woken up.

2. The method according to claim 1, characterized in that The step of determining, for each target grid, the total number of first MR samples of all base stations corresponding to the target grid within a first preset time period includes: Within the first preset time period, collecting first MR data of all base stations according to a preset MR sampling period; Performing rasterization processing on the MR data of the base station to generate a plurality of grids; For each target grid among the multiple grids, the first MR sampling number of each base station corresponding to the target grid is summed to determine the total number of first MR samplings of the target grid.

3. The method according to claim 1 or 2, characterized in that: When the target base station is in a non-sleep state, the method further includes: For each target grid, determining a second MR sampling number and a signal received power RSRP of each base station corresponding to the target grid within a second preset time length; The wake-up index of the target grid is determined according to the second MR sampling number and RSRP of each base station corresponding to the target grid.

4. The method according to claim 3, characterized in that The step of determining the wake-up index of the target grid according to the second MR sampling number and RSRP of each base station corresponding to the target grid includes: Determining the type of the target grid according to the RSRP of each base station corresponding to the target grid; The wake-up index of the target grid is determined according to the type of the target grid and the corresponding second MR sampling number of each base station.

5. The method according to claim 4, characterized in that The step of determining the wake-up index of the target grid according to the type of the target grid and the corresponding second MR sampling number of each base station includes: Determine the total number of second MR samples of all base stations corresponding to the target grid according to the second MR sample number of each base station corresponding to the target grid; For each type, summing up the total number of second MR samplings of the target grids corresponding to the type to obtain the total number of third MR samplings; For each target grid, the awakening index of the target grid is determined according to the total number of second MR samplings and the total number of third MR samplings corresponding to the target grid and a preset weight corresponding to the type of the target grid.

6. The method according to claim 4 or 5, characterized in that: The determining the type of the target grid according to the RSRP of each base station corresponding to the target grid includes: If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and the RSRPs of all neighboring base stations are lower than the preset RSRP, determining that the target grid is of the first type; If the RSRP of the target base station in the target grid is not lower than the preset RSRP, and there is a neighboring base station whose RSRP is not lower than the preset RSRP, determining that the target grid is of the second type; If the RSRP of the target base station in the target grid is less than the preset RSRP, and there is a neighboring base station whose RSRP is not less than the preset RSRP, determining that the target grid is of the third type; The base stations corresponding to the target grid include the target base station and at least one neighboring base station.

7. The method according to claim 3, characterized in that The step of determining, for each target grid, a second MR sampling number and an RSRP of each base station corresponding to the target grid within a second preset time period includes: Within the second preset time period, collecting second MR data of all base stations according to the preset MR sampling period; Performing rasterization processing on the second MR data of all base stations to generate a plurality of grids; For each target grid among the multiple grids, the second MR sampling number and RSRP of each base station corresponding to the target grid are determined according to the second MR data of each base station corresponding to the target grid.

8. The method according to claim 2, characterized in that: The method further comprises: The preset MR sampling number is determined according to the first preset time length and the MR sampling period.

9. A base station wake-up device, characterized in that: include: A first determination module is used to determine, for each target grid, a total number of first MR samples of all base stations corresponding to the target grid within a first preset time period when the target base station is in a dormant state, wherein the target grid is a grid in which the serving base station is the target base station when the target base station is in a non-dormant state; An acquisition module, configured to acquire a wake-up index of the target grid if it is determined that the first MR sampling total number is greater than a preset MR sampling number, wherein the wake-up index is proportional to the degree to which the target base station needs to be awakened; A second determination module is used to sum the wake-up indexes of all target grids to determine a target wake-up index corresponding to the target base station; The wake-up module is used to wake up the target base station if the target wake-up index is greater than a preset wake-up index.

10. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the base station wake-up method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: 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 base station wake-up method according to any one of claims 1 to 8.

12. A computer program product, characterized in that It comprises a computer program, characterized in that when the computer program is executed by a processor, it is used to implement the base station wake-up method as described in any one of claims 1 to 8.

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