Antenna parameter adjustment method and apparatus

Abstract

The embodiment of the present specification discloses an antenna parameter adjustment method and device, which can meet the experience perception demand of users for various service scenarios to the greatest extent without increasing resources. The method comprises the following steps: obtaining user network related data, cell engineering parameters and corresponding service scenarios in a grid of a region to be analyzed; determining steady-state users in the grid and network performance index data of the steady-state users in the grid based on the user network related data in the grid; determining a problem grid of the region to be analyzed based on the network performance index data of the steady-state users in each grid of the region to be analyzed in the corresponding grid; and adjusting cell base station antenna parameters of the problem grid based on the cell engineering parameters and the corresponding service scenarios of the problem grid.

Description

Technical Field

[0001] This document relates to the field of network technology, and in particular to an antenna parameter adjustment method and apparatus. Background Technology

[0002] With the rapid construction and operation of 5G networks, operators face severe challenges in 5G wireless network planning and maintenance under the new circumstances. "Networks move with services," meaning 5G wireless coverage and resource planning need to be adaptively adjusted to meet the diverse needs of users and improve the overall perception of network support capabilities. Optimizing the weight parameters of massive MIMO antennas will directly impact wireless coverage and balance the adjustment and allocation of wireless resources.

[0003] Currently, 5G Massive MIMO antenna adjustment schemes primarily involve antenna selection and parameter setting during wireless network planning. After network activation, MR gridding is performed based on the distribution of 5G user measurement reports (MR) to identify weak coverage areas and pinpoint the base station cells within these areas. Based on these weak coverage regions, antenna transmit power, azimuth angle, and other antenna engineering parameters are adjusted to improve coverage and thus resolve the weak coverage problem in the network.

[0004] The aforementioned traditional Massive MIMO antenna parameter adjustment schemes can only improve network coverage and quality to a certain extent. However, in the face of the diverse service targets and industry needs of 5G networks, they cannot effectively meet the needs of the experience perception of all users and the balanced planning of network resources. Summary of the Invention

[0005] The purpose of the embodiments in this specification is to provide an antenna parameter adjustment method and apparatus that can maximize the user's experience and perception needs for various service scenarios without increasing resources.

[0006] To achieve the above objectives, the embodiments in this specification adopt the following technical solutions:

[0007] Firstly, a method for adjusting antenna parameters is provided, including:

[0008] Acquire user network-related data, cell engineering parameters, and corresponding business scenarios within the grid of the area to be analyzed;

[0009] Based on the user network-related data within the grid, determine the steady-state users within the grid and the network performance index data of the steady-state users within the grid;

[0010] Based on the network performance index data of steady-state users in each grid of the region to be analyzed, the problem grid of the region to be analyzed is determined.

[0011] Based on the cell engineering parameters and corresponding service scenarios of the problematic grid, the base station antenna parameters of the problematic grid are adjusted.

[0012] Secondly, an antenna parameter adjustment device is provided, comprising:

[0013] The first acquisition unit is used to acquire user network-related data, cell engineering parameters, and corresponding business scenarios within the grid of the area to be analyzed.

[0014] The first determining unit is used to determine the steady-state users in the grid and the network performance index data of the steady-state users in the grid based on the user network-related data in the grid.

[0015] The second determining unit is used to determine the problem grid of the region to be analyzed based on the network performance index data of the steady-state users in each grid of the region to be analyzed.

[0016] The antenna parameter adjustment unit is used to adjust the base station antenna parameters of the problematic grid cell based on the cell engineering parameters and corresponding service scenarios of the problematic grid.

[0017] Thirdly, an electronic device is provided, comprising:

[0018] processor;

[0019] Memory used to store the processor's executable instructions;

[0020] The processor is configured to execute the instructions to implement the method as described in the first aspect.

[0021] Fourthly, a computer-readable storage medium is provided, wherein when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method described in the first aspect.

[0022] The solution described in this specification analyzes user network-related data within a grid of the area to be analyzed to determine the steady-state users and their network performance metrics within that grid. Since the network performance metrics of steady-state users within a grid reflect the general service perception of network performance, problem grids within the area to be analyzed can be accurately identified based on the network performance metrics of steady-state users within their respective grids. Based on the cell engineering parameters and corresponding service scenarios of the problem grids, the base station antenna parameters of the problem grids are adjusted to maximize user experience across various service scenarios without increasing resources. Furthermore, the antenna parameter adjustment method described in this specification is independent of equipment manufacturers and base station antenna coverage scenarios, making it applicable across the entire network. Attached Figure Description

[0023] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings:

[0024] Figure 1 A flowchart illustrating an antenna parameter adjustment method provided in one embodiment of this specification;

[0025] Figure 2 A schematic diagram of an antenna parameter adjustment device provided for one embodiment of this specification;

[0026] Figure 3 This is a schematic diagram of an electronic device provided as an embodiment of the present specification. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this document.

[0028] The terms "first," "second," etc., used in this specification and claims are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this specification can be implemented in orders other than those illustrated or described herein. Furthermore, in this specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0029] To address the issue that traditional Massive MIMO antenna parameter adjustment schemes cannot effectively meet the needs of user experience perception and network resource balancing planning for all users, this specification provides an antenna parameter adjustment scheme. By analyzing user network-related data within the grid of the area to be analyzed, the scheme identifies steady-state users within the grid and their network performance metrics. Since the network performance metrics of steady-state users within a grid reflect the general service perception of network performance, problem grids within the area to be analyzed can be accurately identified based on the network performance metrics of steady-state users within their respective grids. Based on the cell engineering parameters and corresponding service scenarios of the problem grids, the base station antenna parameters of the problem grids are adjusted to maximize user experience perception for various service scenarios without increasing resources.

[0030] It should be understood that the antenna parameter adjustment method provided in the embodiments of this specification can be executed by an electronic device or by software installed in an electronic device, specifically by a terminal device or a server device.

[0031] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0032] Please refer to Figure 1 This is a flowchart illustrating an antenna parameter adjustment method according to an embodiment of this specification. The method may include:

[0033] S102, obtain user network-related data, cell engineering parameters, and corresponding business scenarios within the grid of the area to be analyzed.

[0034] In the embodiments of this specification, for each grid within the area to be analyzed, the user network-related data within that grid refers to data that reflects the network performance of the users within that grid. Specifically, this may include, but is not limited to, user call detail record (CDR) signaling data, measurement report (MR) data, and Voice over Long-Term Evolution (VoLTE) data. The user CDR XDR data may include, but is not limited to, S1-U interface signaling data and S1-MME interface signaling data. To make the obtained user network-related data more comprehensive and accurate, in an optional implementation, the user network-related data within the grid of the area to be analyzed can be obtained through the following steps:

[0035] Step A1: Obtain the geographical features of the area to be analyzed and the generated user network-related data.

[0036] Among these factors, whether the geographical features of the area to be analyzed can reflect the types of buildings contained within that area is crucial.

[0037] Step A2: Based on the geographical features of the area to be analyzed, the area to be analyzed is divided into multiple grids.

[0038] Specifically, the area to be analyzed can be divided into three-dimensional grids according to the grid size used for matching geographic features, thus obtaining multiple grids. For example, for high-rise buildings within the area to be analyzed, the high-rise buildings in the area to be analyzed can be divided into grids according to a height of 3 meters, while for the core urban area within the area to be analyzed, the core urban area can be divided into grids according to a grid size of 20*20 meters.

[0039] Step A3: Based on the UE-S1-APID field in the user call detail record (XDR) data and the UE-S1-APID field in the MR data, associate the user call detail record (XDR) data and the MR data.

[0040] It should be noted that associating different data by using the same field in different data is a technique known to those skilled in the art, and will not be elaborated here.

[0041] Step A4: Based on the multiple grids obtained from the division of the area to be analyzed, as well as the associated user call detail record (XDR) data and MR data, determine the grid to which the user network-related data belongs.

[0042] After the user call detail record (XDR) data and MR data are associated, the location information in the MR data can be combined with the S1-U interface signaling data and S1-MME interface signaling data in the user call detail record (XDR) data. Based on the location information in the associated data, user network-related data can be rasterized. After rasterization, the raster to which the user network-related data belongs can be obtained. Statistical analysis can then be performed on the user network-related data within each raster of the area to be analyzed to determine the stable users within each raster and the network performance indicators of stable users within their respective rasteresms.

[0043] In the embodiments of this specification, for each grid within the area to be analyzed, the cell engineering parameters within the grid may include the basic engineering parameters of the primary serving cell within the grid. The basic engineering parameters of the primary serving cell may include, for example, but not limited to: the base station latitude and longitude, antenna azimuth, downtilt angle, site altitude, operating frequency, antenna type, and transmit power of the primary serving cell.

[0044] In the embodiments of this specification, for each grid within the area to be analyzed, the service scenario corresponding to the grid is used to indicate the target of the 5G network service within that grid, such as ToB users, ToC users, etc.

[0045] S104. Based on the user network-related data in each grid, determine the steady-state users in each grid and the network performance index data of the steady-state users in their respective grids.

[0046] In the embodiments of this specification, a steady-state user within a grid refers to a user who appears continuously within that grid for an extended period of time. In an optional implementation, for each grid, cluster analysis can be performed on the S1-MME interface data and Voice Over Long-Term Evolution (VoLTE) data in the XDR (X-Record Data Record) data of each user within that grid to determine the time periods during which each user appears within that grid. Furthermore, users who appear continuously within that grid for a duration exceeding a preset timeframe are identified as steady-state users within that grid. For example, if a user appears within a grid during the same time period for four out of seven days, that user can be identified as a steady-state user within that grid.

[0047] After identifying the steady-state users within each grid of the area to be analyzed, for each grid, the network performance indicators of the steady-state users within that grid can be obtained by analyzing their user network-related data. It should be noted that in practical applications, various techniques known to those skilled in the art can be used to analyze the user network-related data of the steady-state users within a grid to obtain their network performance indicators. This specification does not limit the specific techniques used in the embodiments, and the detailed analysis process will not be elaborated upon here.

[0048] In the embodiments of this specification, the network performance index data of a steady-state user within its assigned grid refers to data that reflects the network performance of the steady-state user within its assigned grid. Optionally, considering the differences in network performance when a user uses different services within the same grid, in order to comprehensively and objectively reflect the network performance within the grid of a steady-state user, the network performance index data of a steady-state user within its assigned grid may include index values ​​of multiple network performance indicators corresponding to various services for the steady-state user. These various services may include, for example, but are not limited to: video services, instant messaging services, navigation services, web browsing services, voice communication services, etc., and the multiple network performance indicators may include, for example, but are not limited to: call completion rate, call drop rate, interference level, latency, data rate, handover success rate, and coverage rate, etc.

[0049] S106. Based on the network performance index data of steady-state users in each grid of the region to be analyzed, determine the problem grid of the region to be analyzed.

[0050] Since the network performance index data of steady-state users within their respective grids refers to data that reflects the network performance of steady-state users within their respective grids, by analyzing the network performance index data of steady-state users within each grid of the area to be analyzed, it is possible to determine whether there are network performance problems in each grid of the area to be analyzed, that is, to identify the problem grids in the area to be analyzed.

[0051] To accurately identify the problem grid in the area to be analyzed, in one optional implementation, S106 may include the following steps:

[0052] Step B1: For various services, based on the indicator values ​​of multiple network performance indicators corresponding to the steady-state users in each grid of the area to be analyzed under the service and the weights of the multiple network performance indicators corresponding to the service, determine the experience perception score of the steady-state users in each grid of the area to be analyzed for the service.

[0053] Specifically, for each steady-state user within each grid of the area to be analyzed, if the value of a certain network performance indicator for that steady-state user under that service is less than the threshold value of that network performance indicator for that service, then the weight of that network performance indicator for that service is determined as the user's perceived experience score for that network performance indicator within that service; otherwise, the user's perceived experience score for that network performance indicator within that service is determined to be 0. Further, by summing the perceived experience scores of the steady-state user within that grid for multiple network performance indicators within that service, the user's perceived experience score for that service within that grid can be obtained.

[0054] It should be noted that the threshold values ​​and weights of various network performance indicators for different services can be set according to actual needs, and the embodiments in this specification do not impose specific limitations on this. For example, Table 1 below shows the threshold values ​​of various network performance indicators under different services, and Table 2 below outputs the weights of various network performance indicators under different services, where S1 to S5 represent the service identifiers of various services, t1 to t7 represent the threshold values ​​of various network performance indicators, and r1 to r7 represent the weights of various network performance indicators.

[0055] Table 1

[0056]

[0057] Table 2

[0058]

[0059] Step B2: Based on the steady-state user experience perception scores for various services in each grid of the area to be analyzed, determine the comprehensive service perception score corresponding to each grid of the area to be analyzed.

[0060] Specifically, for each steady-state user within each grid, the sum of the user's experience perception scores for various services can be determined as the user's service perception score for that grid. Then, the average of the service perception scores of all steady-state users within that grid is determined as the comprehensive service perception score for that grid. That is, the comprehensive service perception score for each grid in the area to be analyzed can be determined by the following formula (1):

[0061]

[0062] Where V represents the comprehensive service perception score corresponding to the grid, ki represents the index value of the i-th user in the k-th network performance index corresponding to the s-th service, tk represents the index threshold of the k-th network performance index corresponding to the s-th service, rk represents the weight of the k-th network performance index corresponding to the s-th service, K represents the number of network performance indexes, m represents the number of services, and n represents the number of steady-state users in the grid.

[0063] Step B3: Identify the grid cells in the area to be analyzed whose comprehensive business perception score exceeds the preset perception score threshold as problem grid cells in the area to be analyzed.

[0064] The preset perception score threshold can be set according to actual needs, and this embodiment does not specifically limit it.

[0065] It is understandable that in the above implementation, when determining the experience perception scores of steady-state users for various services in each grid of the area to be analyzed, the impact of various network performance indicators of steady-state users in each grid on user experience perception is comprehensively considered, making the determined experience perception scores of steady-state users for various services more accurate and objective. Furthermore, based on the experience perception scores of steady-state users for various services in each grid, the comprehensive service perception score corresponding to each grid is determined, comprehensively considering the experience perception of different steady-state users for different services in each grid. Thus, based on the comprehensive service perception score corresponding to each grid, the identified problem grids can reflect the network optimization needs of various users and various services, thereby enabling subsequent adjustments to the cell base station antenna parameters of this problem grid to effectively meet the experience perception needs of various users for various services.

[0066] S108, Based on the cell engineering parameters of the problematic grid and the corresponding service scenario, adjust the base station antenna parameters of the problematic grid.

[0067] In the embodiments of this specification, the cell base station antenna parameters refer to the antenna parameters of the base station antenna of the primary serving cell, which may include, but are not limited to, the built-in downtilt angle of the base station antenna, the antenna scenario type, the base station power, the azimuth angle, and the mechanical downtilt angle.

[0068] To better meet users' experience perception needs in various business scenarios, in one optional implementation, the above S108 may include the following steps:

[0069] Step C1: Based on the relationships between rasters within the area to be analyzed and the business scenarios corresponding to the rasters, cluster problem rasters with the same business scenarios to obtain multiple clustered regions.

[0070] In the embodiments of this specification, the relationships between grids within the area to be analyzed can ensure whether the grids are adjacent. By clustering adjacent problem grids with the same business scenario, multiple clustering regions can be obtained, and each clustering region includes at least one problem grid. The relationships between grids within the area to be analyzed can be obtained when dividing the area into grids, and will not be described in detail here.

[0071] Step C2: Select the cluster regions containing more than a preset threshold number of problem grids from multiple cluster regions as the problem regions to be optimized.

[0072] The more problem grids a cluster contains, the worse the user's perception of the business experience within that cluster. Based on this, clusters containing more than a preset threshold of problem grids can be identified as problem areas that need to be optimized.

[0073] In the embodiments of this specification, the preset quantity threshold can be set according to actual needs, and this specification does not impose specific limitations on it. For example, the preset quantity threshold can be set to 5.

[0074] Step C3: Based on the cell engineering parameters of the problem grid within the problem area to be optimized, adjust the base station antenna parameters of the problem area.

[0075] Specifically, the antenna-related parameters of the primary serving cell in the problem area can be fed back via the southbound interface to form a list of base station antenna parameters (such as 5G Massive MIMO antennas) for the primary serving cell. Based on the basic engineering parameters of the primary serving cell, the parameters of its base station antennas can then be adjusted. More specifically, to better meet users' needs for wireless resources, when adjusting the base station antenna parameters of the primary serving cell, the current wireless resource index data of the primary serving cell can be determined based on its basic engineering parameters and current base station antenna parameters. Then, based on the current wireless resource index data of the primary serving cell in the problem area and the preset wireless resource requirements, the current base station antenna parameters of the primary serving cell can be adjusted to ensure that the wireless resources in the problem area meet the preset requirements.

[0076] In practice, the base station antenna parameters of the primary serving cell can be adjusted based on the difference between the current radio resource index data and the preset radio resource requirements. The radio resource index data of the primary serving cell after the base station antenna parameter adjustment can be obtained again. If the preset radio resource requirements are still not met, the above process is repeated until the radio resource index data of the primary serving cell meets the preset radio resource requirements.

[0077] It should be noted that the radio resource index data of the primary serving cell refers to data reflecting the radio resource usage of the primary serving cell, and the specific data can be selected according to actual needs. This specification does not impose specific limitations on this selection in the embodiments. Furthermore, the current radio resource index data of the primary serving cell can be determined using various technical means known to those skilled in the art, and this specification does not impose specific limitations on this selection in the embodiments.

[0078] Considering that in actual implementation, the base station antenna parameters of the primary serving cell may need to be adjusted multiple times to meet the requirements, in order to reduce the number of times the base station antenna parameters of the primary serving cell need to be adjusted, the optimal adjustment scheme for the base station antenna parameters of the primary serving cell can be determined through simulation analysis. Then, the base station antenna can be adjusted based on the optimal adjustment scheme to save adjustment costs and improve adjustment efficiency.

[0079] Specifically, determining the current radio resource index data of the primary serving cell includes: establishing a base station antenna model of the primary serving cell based on the basic engineering parameters and current base station antenna parameters of the primary serving cell in the problem area; and performing radio resource simulation analysis based on the base station antenna model of the primary serving cell to obtain the current radio resource index data of the primary serving cell.

[0080] Accordingly, the current base station antenna parameters of the primary serving cell are adjusted, including: if the current radio resource index data of the primary serving cell does not meet the preset radio resource requirements, the current radio resource index data of the primary serving cell is updated; the above steps of establishing the base station antenna model of the primary serving cell based on the current radio resource index data of the primary serving cell and the preset radio resource requirements are repeated until the current radio resource index data of the primary serving cell meets the radio resource requirements; furthermore, the base station antenna parameters when the current radio resource index data of the primary serving cell meets the radio resource requirements are determined as the target antenna parameters, and the base station antenna parameters of the primary serving cell are adjusted based on the target antenna parameters.

[0081] It should be noted that the establishment of base station antenna models and the simulation analysis of wireless resources can be achieved through modeling and analysis methods known to those skilled in the art, and the embodiments in this specification do not specifically limit this.

[0082] To further improve the effectiveness of base station antenna parameter adjustment in problem areas and better meet users' experience and perception needs for various service scenarios, in another embodiment of this specification, after adjusting the current base station antenna parameters of the primary serving cell based on the current radio resource index data and preset radio resource requirements in S108, the antenna parameter adjustment method provided in this embodiment may further include: for the problem area, acquiring user network-related data of the problem grid within the problem area again, and determining the network performance index data of the steady-state users within the problem grid after antenna parameter adjustment based on the user network-related data of the problem grid; then, based on the network performance index data of the steady-state users within the problem grid before and after antenna parameter adjustment, determining whether the antenna parameter adjustment of the problem area has reached the preset adjustment target; if not, repeating the above steps of adjusting the cell base station antenna parameters of the problem grid based on the cell engineering parameters and corresponding service scenarios of the problem grid until the antenna parameter adjustment of the problem area reaches the adjustment target.

[0083] In the embodiments of this specification, the above-mentioned adjustment target can be preset according to actual needs, and this specification does not specifically limit it. For example, the above-mentioned adjustment target can be set to improve the network performance index data of steady-state users in the problem grid within the problem area after antenna parameter adjustment compared to the network performance index data before antenna parameter adjustment. Alternatively, the above-mentioned adjustment target can also be set to reduce the number of problem grids in the problem area after antenna parameter adjustment compared to the number of problem grids before strip parameter adjustment.

[0084] The antenna parameter adjustment method provided in one or more embodiments of this specification analyzes user network-related data within a grid of the area to be analyzed to determine the steady-state users and their network performance indicators within the grid. Since the network performance indicators of steady-state users within a grid reflect the general service perception of network performance within that grid, problem grids in the area to be analyzed can be accurately identified based on the network performance indicators of steady-state users within their respective grids. Based on the cell engineering parameters and corresponding service scenarios of the problem grids, the base station antenna parameters of the problem grid cells are adjusted to maximize user experience and perception requirements for various service scenarios without increasing resources. Furthermore, the antenna parameter adjustment method in the embodiments of this specification is independent of equipment manufacturers and base station antenna coverage scenarios, and has the basis for widespread application across the entire network.

[0085] In addition, with the above Figure 1Corresponding to the antenna parameter adjustment method shown, this specification also provides an antenna parameter adjustment device in its embodiments. Figure 2 This is a schematic diagram of the structure of an antenna parameter adjustment device 200 provided in the embodiments of this specification, including:

[0086] The first acquisition unit 210 is used to acquire user network-related data, cell engineering parameters and corresponding business scenarios within the grid of the area to be analyzed.

[0087] The first determining unit 220 is used to determine the steady-state users in the grid and the network performance index data of the steady-state users in the grid based on the user network-related data in the grid.

[0088] The second determining unit 230 is used to determine the problem grid of the region to be analyzed based on the network performance index data of the steady-state users in each grid of the region to be analyzed.

[0089] The antenna parameter adjustment unit 240 is used to adjust the base station antenna parameters of the problematic grid cell based on the cell engineering parameters and corresponding service scenarios of the problematic grid.

[0090] The antenna parameter adjustment device provided in this specification analyzes the acquired user network-related data within a grid of the area to be analyzed to determine the steady-state users within the grid and their network performance indicators. Since the network performance indicators of steady-state users within a grid reflect the general service perception of network performance within that grid, problem grids in the area to be analyzed can be accurately identified based on the network performance indicators of steady-state users within their respective grids. Based on the cell engineering parameters and corresponding service scenarios of the problem grids, the base station antenna parameters of the problem grids are adjusted to maximize user experience and perception for various service scenarios without increasing resources. Furthermore, the antenna parameter adjustment method in this specification is independent of equipment manufacturers and base station antenna coverage scenarios, and has the foundation for widespread application across the entire network.

[0091] Optionally, the network performance index data includes the index values ​​of multiple network performance indicators for the steady-state user under various services;

[0092] The second determining unit 230 includes:

[0093] The experience perception score determination subunit is used to determine the experience perception score of the steady-state users in each grid of the region to be analyzed for the service, based on the index values ​​of multiple network performance indicators corresponding to the steady-state users in each grid of the region to be analyzed under the service and the weights of the multiple network performance indicators corresponding to the service.

[0094] The comprehensive service perception score determination subunit is used to determine the comprehensive service perception score corresponding to each grid in the region to be analyzed based on the steady-state user experience perception scores for the various services in each grid of the region to be analyzed.

[0095] The problem grid determination sub-unit is used to identify grids in the area to be analyzed whose comprehensive business perception score exceeds a preset perception score threshold as problem grids in the area to be analyzed.

[0096] Optionally, the antenna parameter adjustment unit 240 includes:

[0097] The clustering subunit is used to cluster problem grids with the same business scenario based on the relationship between grids in the area to be analyzed and the business scenario corresponding to the grid, so as to obtain multiple clustering areas.

[0098] The problem region selection sub-unit is used to select from the multiple cluster regions a cluster region containing more than a preset number threshold of problem grids as the problem region to be optimized.

[0099] The adjustment subunit is used to adjust the base station antenna parameters of the problem area based on the cell engineering parameters of the problem grid within the problem area to be optimized.

[0100] Optionally, the cell engineering parameters include the basic engineering parameters of the primary serving cell;

[0101] The adjustment subunit is specifically used for:

[0102] Based on the basic engineering parameters of the primary serving cell in the problem area and the current base station antenna parameters, determine the current radio resource index data of the primary serving cell;

[0103] Based on the current radio resource index data and preset radio resource requirements of the primary serving cell, the current base station antenna parameters of the primary serving cell are adjusted.

[0104] Optionally, the adjustment subunit is specifically used for:

[0105] Based on the basic engineering parameters of the primary serving cell in the problem area and the current base station antenna parameters, a base station antenna model of the primary serving cell is established.

[0106] Based on the base station antenna model of the primary serving cell, a wireless resource simulation analysis is performed to obtain the current wireless resource index data of the primary serving cell.

[0107] If the current radio resource index data of the primary serving cell does not meet the radio resource requirements, then the current radio resource index data of the primary serving cell is updated.

[0108] Repeat the steps of establishing a base station antenna model of the primary serving cell based on the current radio resource index data and preset radio resource requirements, and then performing radio resource simulation analysis based on the base station antenna model of the primary serving cell, until the current radio resource index data of the primary serving cell meets the radio resource requirements.

[0109] The base station antenna parameters when the current radio resource index data of the primary serving cell meets the radio resource requirements are determined as the target antenna parameters;

[0110] Based on the target antenna parameters, the base station antenna parameters of the primary serving cell are adjusted.

[0111] Optionally, the first acquisition unit 210 is further configured to, after the adjustment subunit adjusts the current base station antenna parameters of the main serving cell based on the current radio resource index data of the main serving cell and the preset radio resource requirements, acquire again the user network related data of the problem grid in the problem area for the problem area.

[0112] The first determining unit 220 is further configured to determine, based on the user network-related data of the problem grid, the network performance index data of the steady-state users in the problem grid after antenna parameter adjustment;

[0113] The device further includes:

[0114] The third determining unit is used to determine whether the antenna parameter adjustment of the problem area has achieved the preset adjustment target based on the network performance index data of steady-state users in the problem grid within the problem area before and after the antenna parameter adjustment.

[0115] The repeated adjustment unit is used to repeatedly execute the step of adjusting the cell base station antenna parameters of the problem grid based on the cell engineering parameters and corresponding service scenarios of the problem grid if the adjustment of the antenna parameters of the problem area does not reach the preset adjustment target, until the adjustment of the antenna parameters of the problem area reaches the adjustment target.

[0116] Optionally, the first acquisition unit 210 includes:

[0117] The first acquisition subunit is used to acquire the geographical features of the area to be analyzed and the generated user network related data, the user network related data including user call detail record (XDR) data and measurement report (MR) data.

[0118] The grid division sub-unit is used to divide the area to be analyzed into multiple grids based on the geographical features of the area to be analyzed;

[0119] The association subunit is used to associate the user call detail record (XDR) data and the MR data based on the UE-S1-APID field in the user call detail record (XDR) data and the UE-S1-APID field in the MR data.

[0120] The grid determination subunit is used to determine the grid to which the user network-related data belongs based on multiple grids obtained by dividing the area to be analyzed, as well as the associated user call detail record (XDR) data and the MR data.

[0121] Obviously, the antenna parameter adjustment device in the embodiments of this specification can be used as described above. Figure 1 The entity executing the antenna parameter adjustment method shown is therefore capable of implementing the antenna parameter adjustment method in... Figure 1 The functions implemented are the same, so they will not be described in detail here.

[0122] Figure 3 This is a schematic diagram of the structure of an electronic device according to one embodiment of this specification. Please refer to it. Figure 3 At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for other business operations.

[0123] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0124] Memory is used to store programs. Specifically, programs may include program code, which includes computer operation instructions. Memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0125] The processor reads the corresponding computer program from non-volatile memory into main memory and then runs it, forming the antenna parameter adjustment device at the logical level. The processor executes the program stored in memory and specifically performs the following operations:

[0126] Acquire user network-related data, cell engineering parameters, and corresponding business scenarios within the grid of the area to be analyzed;

[0127] Based on the user network-related data within the grid, determine the steady-state users within the grid and the network performance index data of the steady-state users within the grid;

[0128] Based on the network performance index data of steady-state users in each grid of the region to be analyzed, the problem grid of the region to be analyzed is determined.

[0129] Based on the cell engineering parameters and corresponding service scenarios of the problematic grid, the base station antenna parameters of the problematic grid are adjusted.

[0130] The above is as described in this instruction manual. Figure 1The method executed by the antenna parameter adjustment device disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this specification. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this specification can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0131] It should be understood that the electronic device in the embodiments of this specification can realize the antenna parameter adjustment device in Figure 1 The embodiments shown have the same function. Since the principle is the same, the embodiments in this specification will not be described again here.

[0132] Of course, in addition to software implementation, the electronic device described in this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0133] This specification also provides an embodiment of a computer-readable storage medium that stores one or more programs, the programs including instructions that, when executed by a portable electronic device including multiple applications, enable the portable electronic device to perform... Figure 1 The method of the illustrated embodiment is specifically used to perform the following operations:

[0134] Acquire user network-related data, cell engineering parameters, and corresponding business scenarios within the grid of the area to be analyzed;

[0135] Based on the user network-related data within the grid, determine the steady-state users within the grid and the network performance index data of the steady-state users within the grid;

[0136] Based on the network performance index data of steady-state users in each grid of the region to be analyzed, the problem grid of the region to be analyzed is determined.

[0137] Based on the cell engineering parameters and corresponding service scenarios of the problematic grid, the base station antenna parameters of the problematic grid are adjusted.

[0138] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0139] In summary, the above description is merely a preferred embodiment of this specification and is not intended to limit the scope of protection of this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of protection of this specification.

[0140] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a computer.

[0141] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0142] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0143] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

Claims

1. A method for adjusting antenna parameters, characterized in that, include: Acquire user network-related data, cell engineering parameters, and corresponding service scenarios within the grid of the area to be analyzed. The service scenario corresponding to the grid is used to indicate the target of the 5G network service within the grid. Based on the user network-related data within the grid, the steady-state users within the grid and the network performance index data of the steady-state users within the grid are determined. The network performance index data includes the index values ​​of the steady-state users corresponding to multiple network performance indicators under various services. Based on the network performance index data of steady-state users in each grid of the region to be analyzed, problem grids in the region to be analyzed are determined. The problem grids are determined based on the comprehensive service perception scores corresponding to each grid in the region to be analyzed. The comprehensive service perception scores corresponding to the grids are determined in the following way: based on the impact of various network performance indicators of steady-state users in the grid on user experience perception, the experience perception scores of steady-state users in the grid for various services are determined, and based on the experience perception scores, the comprehensive service perception score corresponding to the grid is determined. Based on the cell engineering parameters and corresponding service scenarios of the problematic grid, the base station antenna parameters of the problematic grid are adjusted.

2. The method according to claim 1, characterized in that, The process of determining the problem grids in the region to be analyzed based on the network performance index data of steady-state users within their respective grids includes: For each of the various services, based on the index values ​​of multiple network performance indicators corresponding to the steady-state users in each grid of the region to be analyzed under the service and the weights of the multiple network performance indicators corresponding to the service, the experience perception score of the steady-state users in each grid of the region to be analyzed for the service is determined. Based on the steady-state user experience perception scores for the various services in each grid of the region to be analyzed, the comprehensive service perception score corresponding to each grid of the region to be analyzed is determined. The grid cells in the area to be analyzed whose comprehensive business perception score exceeds the preset perception score threshold are identified as problem grid cells in the area to be analyzed.

3. The method according to claim 1, characterized in that, The adjustment of cell base station antenna parameters based on the cell engineering parameters and corresponding service scenarios of the problem grid includes: Based on the relationships between grids within the area to be analyzed and the business scenarios corresponding to the grids, problem grids with the same business scenarios are clustered to obtain multiple clustered areas. From the multiple clustering regions, select the clustering region containing more than a preset number of problem grids as the problem region to be optimized; Based on the cell engineering parameters of the problem grid within the problem area to be optimized, the base station antenna parameters of the problem area are adjusted.

4. The method according to claim 3, characterized in that, The engineering parameters of the community include the basic engineering parameters of the primary serving cell; The adjustment of base station antenna parameters in the problem area based on the cell engineering parameters of the problem grid within the problem area to be optimized includes: Based on the basic engineering parameters of the primary serving cell in the problem area and the current base station antenna parameters, determine the current radio resource index data of the primary serving cell; Based on the current radio resource index data and preset radio resource requirements of the primary serving cell, the current base station antenna parameters of the primary serving cell are adjusted.

5. The method according to claim 4, characterized in that, The determination of the current radio resource index data of the primary serving cell based on the basic engineering parameters of the primary serving cell and the current base station antenna parameters in the problem area includes: Based on the basic engineering parameters of the primary serving cell in the problem area and the current base station antenna parameters, a base station antenna model of the primary serving cell is established. Based on the base station antenna model of the primary serving cell, a wireless resource simulation analysis is performed to obtain the current wireless resource index data of the primary serving cell. The adjustment of the base station antenna parameters of the primary serving cell based on the current radio resource index data and preset radio resource requirements includes: If the current radio resource index data of the primary serving cell does not meet the radio resource requirements, then the current radio resource index data of the primary serving cell is updated. Repeat the steps of establishing a base station antenna model of the primary serving cell based on the current radio resource index data and preset radio resource requirements, and then performing radio resource simulation analysis based on the base station antenna model of the primary serving cell, until the current radio resource index data of the primary serving cell meets the radio resource requirements. The base station antenna parameters when the current radio resource index data of the primary serving cell meets the radio resource requirements are determined as the target antenna parameters; Based on the target antenna parameters, the base station antenna parameters of the primary serving cell are adjusted.

6. The method according to claim 4, characterized in that, After adjusting the base station antenna parameters of the primary serving cell based on the current radio resource index data and preset radio resource requirements, the method further includes: For the problem area, obtain the user network-related data of the problem grid within the problem area again; Based on the user network-related data of the problem grid, determine the network performance index data of the steady-state users in the problem grid after antenna parameter adjustment; Based on the network performance data of steady-state users in the problem grid within the problem area before and after antenna parameter adjustment, it is determined whether the antenna parameter adjustment in the problem area has achieved the preset adjustment target. If not, repeat the step of adjusting the cell base station antenna parameters of the problem grid based on the cell engineering parameters and corresponding service scenarios of the problem grid until the antenna parameters of the problem area are adjusted to the adjustment target.

7. The method according to any one of claims 1 to 6, characterized in that, The acquisition of user network-related data within the raster of the area to be analyzed includes: The geographical features of the area to be analyzed and the generated user network-related data are obtained, including user call detail records (XDR) data and measurement report (MR) data. Based on the geographical features of the region to be analyzed, the region to be analyzed is divided into multiple grids; Based on the UE-S1-APID field in the user call detail record (XDR) data and the UE-S1-APID field in the MR data, the user call detail record (XDR) data and the MR data are associated. Based on the multiple grids obtained by dividing the area to be analyzed, as well as the associated user call detail record (XDR) data and MR data, the grid to which the user network-related data belongs is determined.

8. An antenna parameter adjustment device, characterized in that, include: The first acquisition unit is used to acquire user network-related data, cell engineering parameters and corresponding service scenarios within the grid of the area to be analyzed. The service scenario corresponding to the grid is used to indicate the target of the 5G network service within the grid. The first determining unit is used to determine the steady-state users in the grid and the network performance index data of the steady-state users in the grid based on the user network-related data in the grid. The network performance index data includes the index values ​​of the steady-state users corresponding to multiple network performance indicators under various services. The second determining unit is used to determine the problem grid of the region to be analyzed based on the network performance index data of the steady-state users in each grid of the region to be analyzed. The antenna parameter adjustment unit is used to adjust the base station antenna parameters of the problem grid cell based on the cell engineering parameters and corresponding service scenarios of the problem grid. The problem grid is determined based on the comprehensive service perception score corresponding to each grid in the area to be analyzed. The comprehensive service perception score corresponding to the grid is determined in the following way: based on the impact of various network performance indicators of steady-state users in the grid on user experience perception, the experience perception score of steady-state users in the grid for various services is determined, and based on the experience perception score, the comprehensive service perception score corresponding to the grid is determined.

9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform the method as described in any one of claims 1 to 7.

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