Network coverage optimization method and device and storage medium

Abstract

The invention provides a network coverage optimization method and device and a storage medium. The method comprises the following steps: acquiring MDT data of a backflow cell and terminal capability information of a terminal in the backflow cell; the backflow cell is a cell of the first standard network; screening the MDT data of the backflow cell according to the terminal capability information and the terminal network login record information, and obtaining latitude and longitude information of a plurality of sampling points corresponding to the backflow terminal from the screened MDT data; the backflow terminal is a terminal which supports a second system network and has a second system network login record in the backflow cell, and the system of the second system network is higher than that of the first system network; and according to the latitude and longitude information of the plurality of sampling points, determining a second type network weak coverage point location in the backflow cell, the second type network weak coverage point location being used for network coverage optimization. The method is not only high in efficiency and low in cost, but also more accurate in judgment of the weak coverage point location of the second system network.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a network coverage optimization method, device and storage medium. Background Art

[0002] In the interoperation between the fifth generation mobile communication technology (5G) and the fourth generation mobile communication technology (4G), the reference signal receiving power (RSRP) is generally used as the decision condition. When the 5G RSRP signal received by the terminal is weaker than a certain threshold, it will go to the 4G network through switching, reselection, redirection, etc. In the process of 5G network construction and development, there is a problem that the terminal is unstable in the 5G network due to insufficient 5G network coverage, and goes to the 4G network through switching, reselection or redirection.

[0003] In order to allow users to stay in the 5G network more stably and ensure the user's perceived experience, it is necessary to accurately know the location areas where 5G users are unstable. The existing technology mainly extracts the backflow ratio index of the background through the network management, screens out the high backflow sites or communities, and then goes to the site for on-site survey. By observing the residential areas, schools, shopping malls and other scenes where major personnel gather around the community, the location areas where users are unstable are determined, and the azimuth of the antenna is adjusted to these location areas. This method requires on-site survey, which is inefficient and costly. In addition, the accuracy is low because the location areas where users are unstable are inferred based on the subjective scenes of major personnel gathering such as residential areas, schools, shopping malls, etc. Summary of the invention

[0004] In view of the problems existing in the prior art, the present application provides a network coverage optimization method, device and storage medium.

[0005] In a first aspect, the present application provides a network coverage optimization method, comprising:

[0006] Acquire the Minimization of Drive Tests (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; the reverse flow cell is a cell of the first standard network;

[0007] The MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, and the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal is obtained from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network;

[0008] According to the latitude and longitude information of multiple sampling points, the weak coverage points of the second standard network in the reverse flow cell are determined, and the weak coverage points of the second standard network are used for network coverage optimization.

[0009] In some embodiments, the MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, including:

[0010] According to the terminal capability information and the terminal login record information, the reverse flow terminal is screened out from the terminals in the reverse flow cell;

[0011] The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

[0012] In some embodiments, determining the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points includes:

[0013] The points corresponding to the latitude and longitude coordinates of multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the location of the newly planned second-standard network site.

[0014] In some embodiments, determining the center position of the weak coverage point of the second standard network includes:

[0015] The kernel density estimation algorithm is used to determine the average center point of the weak coverage points of the second standard network;

[0016] The average center point is determined as the center position of the weak coverage point of the second standard network.

[0017] In some embodiments, the kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

[0018] In some embodiments, the first standard network is a 4G network, and the second standard network is a 5G network.

[0019] In some embodiments, adjusting the coverage position of an existing second-standard network site includes:

[0020] When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth coverage center position of the NR 700M site cell;

[0021] The NR2.6G site cell is a cell of the NR 2.6G site that is within the first distance range around the center position and is closest to the center position; the NR 700M site cell is a cell of the NR 700M site that is within the second distance range around the center position and is closest to the center position.

[0022] In some embodiments, adjusting the beam normal of a new radio interface NR 2.6G site cell to point to a center position, or adjusting the azimuth coverage center position of an NR 700M site cell includes:

[0023] If there is an NR 2.6G site within the first distance range around the center position, adjust the beam normal of the NR 2.6G site cell to point to the center position;

[0024] If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, adjust the azimuth angle of the NR 700M site cell to cover the center position.

[0025] In some embodiments, the beam normal includes a normal of a synchronization signal block (SSB) beam and a normal of a channel state information (CSI) beam.

[0026] In a second aspect, the present application also provides an electronic device, including a memory, a transceiver, and a processor;

[0027] A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations:

[0028] Acquire the Minimization of Drive Tests (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; the reverse flow cell is a cell of the first standard network;

[0029] The MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, and the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal is obtained from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network;

[0030] According to the latitude and longitude information of multiple sampling points, the weak coverage points of the second standard network in the reverse flow cell are determined, and the weak coverage points of the second standard network are used for network coverage optimization.

[0031] In some embodiments, the MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, including:

[0032] According to the terminal capability information and the terminal login record information, the reverse flow terminal is screened out from the terminals in the reverse flow cell;

[0033] The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

[0034] In some embodiments, determining the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points includes:

[0035] The points corresponding to the latitude and longitude coordinates of multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the location of the newly planned second-standard network site.

[0036] In some embodiments, determining the center position of the weak coverage point of the second standard network includes:

[0037] The kernel density estimation algorithm is used to determine the average center point of the weak coverage points of the second standard network;

[0038] The average center point is determined as the center position of the weak coverage point of the second standard network.

[0039] In some embodiments, the kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

[0040] In some embodiments, the first standard network is a 4G network, and the second standard network is a 5G network.

[0041] In some embodiments, adjusting the coverage position of an existing second-standard network site includes:

[0042] When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth coverage center position of the NR 700M site cell;

[0043] The NR2.6G site cell is a cell of the NR 2.6G site that is within the first distance range around the center position and is closest to the center position; the NR 700M site cell is a cell of the NR 700M site that is within the second distance range around the center position and is closest to the center position.

[0044] In some embodiments, adjusting the beam normal of a new radio interface NR 2.6G site cell to point to a center position, or adjusting the azimuth coverage center position of an NR 700M site cell includes:

[0045] If there is an NR 2.6G site within the first distance range around the center position, adjust the beam normal of the NR 2.6G site cell to point to the center position;

[0046] If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, adjust the azimuth angle of the NR 700M site cell to cover the center position.

[0047] In some embodiments, the beam normal includes a normal of a synchronization signal block (SSB) beam and a normal of a channel state information (CSI) beam.

[0048] In a third aspect, the present application also provides a network coverage optimization device, including:

[0049] An acquisition unit, used to acquire the Minimization of Drive Tests (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; the reverse flow cell is a cell of the first standard network;

[0050] A screening unit is used to screen the MDT data of the reverse flow cell according to the terminal capability information and the terminal login record information, and obtain the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network;

[0051] The determination unit is used to determine the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points, and the second standard network weak coverage point is used for network coverage optimization.

[0052] In some embodiments, the MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, including:

[0053] According to the terminal capability information and the terminal login record information, the reverse flow terminal is screened out from the terminals in the reverse flow cell;

[0054] The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

[0055] In some embodiments, determining the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points includes:

[0056] The points corresponding to the latitude and longitude coordinates of multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the location of the newly planned second-standard network site.

[0057] In some embodiments, determining the center position of the weak coverage point of the second standard network includes:

[0058] The kernel density estimation algorithm is used to determine the average center point of the weak coverage points of the second standard network;

[0059] The average center point is determined as the center position of the weak coverage point of the second standard network.

[0060] In some embodiments, the kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

[0061] In some embodiments, the first standard network is a 4G network, and the second standard network is a 5G network.

[0062] In some embodiments, adjusting the coverage position of an existing second-standard network site includes:

[0063] When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth coverage center position of the NR 700M site cell;

[0064] The NR2.6G site cell is a cell of the NR 2.6G site that is within the first distance range around the center position and is closest to the center position; the NR 700M site cell is a cell of the NR 700M site that is within the second distance range around the center position and is closest to the center position.

[0065] In some embodiments, adjusting the beam normal of a new radio interface NR 2.6G site cell to point to a center position, or adjusting the azimuth coverage center position of an NR 700M site cell includes:

[0066] If there is an NR 2.6G site within the first distance range around the center position, adjust the beam normal of the NR 2.6G site cell to point to the center position;

[0067] If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, adjust the azimuth angle of the NR 700M site cell to cover the center position.

[0068] In some embodiments, the beam normal includes a normal of a synchronization signal block (SSB) beam and a normal of a channel state information (CSI) beam.

[0069] In a fourth aspect, the present application further provides a non-transitory readable storage medium, wherein the non-transitory readable storage medium stores a computer program, wherein the computer program is used to enable a processor to execute the network coverage optimization method described in the first aspect as described above.

[0070] In a fifth aspect, the present application further provides a communication device, in which a computer program is stored, and the computer program is used to enable the communication device to execute the network coverage optimization method described in the first aspect as described above.

[0071] In a sixth aspect, the present application also provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the network coverage optimization method described in the first aspect as described above.

[0072] In a seventh aspect, the present application further provides a chip product, wherein a computer program is stored in the chip product, and the computer program is used to enable the chip product to execute the network coverage optimization method described in the first aspect as described above.

[0073] The network coverage optimization method, device and storage medium provided in the present application screen and analyze the MDT data of the reverse flow cell according to the terminal capability information and network login record information of the terminal, obtain the latitude and longitude information of the sampling point corresponding to the reverse flow terminal, and use this to determine the weak coverage points of the second-standard network in the reverse flow cell without the need for on-site investigation. It is not only efficient and low-cost, but also more accurate in judging the weak coverage points of the second-standard network. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the following is a brief introduction to the drawings required for use in the embodiments or the related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0075] Figure 1 A schematic diagram of the 5G network coverage optimization process provided for related technologies;

[0076] Figure 2 A flowchart of a network coverage optimization method provided in an embodiment of the present application;

[0077] Figure 3 An example diagram of the kernel density estimation algorithm processing process provided in an embodiment of the present application;

[0078] Figure 4 A diagram showing various kernel function curve examples provided in the embodiments of the present application;

[0079] Figure 5 An example diagram of network coverage optimization provided in an embodiment of the present application;

[0080] Figure 6 A flowchart of the network coverage optimization method implementation provided in the embodiment of the present application;

[0081] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0082] Figure 8 A schematic diagram of the structure of a network coverage optimization device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0083] In the embodiments of the present application, the term "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0084] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0085] In the embodiments of the present application, the terms "first", "second", etc. are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first" and "second" are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0086] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0087] Figure 1 A schematic diagram of the 5G network coverage optimization process provided for related technologies, such as Figure 1 As shown, the relevant technology mainly extracts the background backflow ratio index through the network management, screens out 5G high backflow sites or communities, and then goes to the site for on-site investigation, by observing the residential areas, schools, shopping malls and other scenes where major personnel gather around the community, determines the location areas where users are unstable, and then adjusts the azimuth angle of the antenna to these location areas.

[0088] However, Figure 1The processing process shown not only requires on-site investigation, which is time-consuming, costly and inefficient; moreover, since the user's location is actually mobile at any time and will not be fixed in a certain location, and considering the market penetration rate of operators, not everyone is a user of the same operator, so the accuracy is low by subjectively judging the 5G backflow user area through on-site investigation of user-concentrated scenarios such as residential areas and schools.

[0089] In response to the above problems, the embodiments of the present application provide a solution that can optimize network coverage more efficiently, cost-effectively and accurately.

[0090] Figure 2 A schematic diagram of a flow chart of a network coverage optimization method provided in an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0091] Step 200: Obtaining Minimization of Drive Tests (MDT) data of a reverse flow cell and terminal capability information of terminals in the reverse flow cell; the reverse flow cell is a cell of a first standard network.

[0092] Specifically, the executor of each step in the method can be a network coverage optimization device, which can be implemented by software and / or hardware. The device can be integrated in an electronic device, which can be a terminal device (such as a smart phone, a personal computer, etc.), or a server (such as a local server or a cloud server, or a server cluster, etc.), or a network device (for example: a base station) or other device.

[0093] A reverse flow cell refers to a low-standard network cell in a multi-standard network coverage area where the traffic of terminals supporting high-standard networks exceeds a certain threshold or a certain proportion. For example, in an area covered by both 5G and 4G networks, if the average daily traffic of 5G terminals on a certain 4G cell exceeds a certain threshold, the 4G cell can be listed as a reverse flow cell. A reverse flow cell can also be called a high reverse flow cell, a high fallback cell, etc.

[0094] The specific method of screening the reverse flow cells can refer to the existing solutions, which will not be described in detail here. For example, the back-end reverse flow ratio index can be extracted through the network management to screen out the reverse flow cell list.

[0095] After discovering the reverse flow cell, the network coverage optimization device can extract the minimized drive test (MDT) data of the reverse flow cell and obtain the terminal capability information of the terminal in the reverse flow cell. The terminal capability information includes information about the networks supported by the terminal, and the networks supported by the terminal can be determined based on the information.

[0096] Step 201: Filter the MDT data of the reverse flow cell according to the terminal capability information and the terminal login record information, and obtain the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal from the filtered MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second-standard network and has a second-standard network login record, and the second-standard network is higher than the first-standard network.

[0097] Specifically, after obtaining the MDT data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell, the network coverage optimization device can use the terminal capability information and the terminal login record information to filter the MDT data of the reverse flow cell, so as to obtain the latitude and longitude information of multiple sampling points (i.e., MDT data sampling points) corresponding to the reverse flow terminal. Among them, the terminal login record information includes the login record of the terminal, and the network that the terminal has logged in can be determined based on the information.

[0098] In the embodiments of the present application, there is no limitation on the specific manner in which the network coverage optimization device obtains MDT data, terminal capability information, and terminal login record information. For example, the data or information may be obtained from other devices storing the data or information, or the data or information may be reported by a user, or may be obtained through other means.

[0099] In the embodiment of the present application, there is no restriction on which network the first standard network and the second standard network belong to, as long as the standard of the second standard network is higher than that of the first standard network. For example, the first standard network can be a 2G network, a 3G network or a 4G network, and the second standard network can be a 5G network or a 6G network; the first standard network can be a 5G network, and the second standard network can be a 6G network; the first standard network can be a 3G network, and the second standard network can be a 4G network, and so on.

[0100] For the sake of convenience, the following text mainly uses the scenario of 5G terminal backflow to 4G cell as an example, that is, the first standard network is 4G network and the second standard network is 5G network. Of course, this is only an example and does not constitute a limitation on the technical solution. The scenarios of other standard networks can also be implemented with reference.

[0101] In some embodiments, the MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, including:

[0102] According to the terminal capability information and the terminal login record information, the reverse flow terminal is screened out from the terminals in the reverse flow cell;

[0103] The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

[0104] For example, when filtering the MDT data of a 4G reverse flow cell, you can first analyze which terminals in the 4G reverse flow cell support 5G based on the terminal capability information. If some terminals support 5G and have 5G network access records, it is considered that these terminals go to the 4G network because the 5G network signal is weak and cannot be stably resident. These terminals can be considered reverse flow terminals. Then, the MDT data of these reverse flow terminals can be filtered out from the MDT data of the 4G reverse flow cell, and the latitude and longitude information of the sampling point corresponding to the reverse flow terminal can be obtained.

[0105] Step 202: Determine the weak coverage points of the second standard network in the reverse flow cell according to the latitude and longitude information of the plurality of sampling points, and the weak coverage points of the second standard network are used for network coverage optimization.

[0106] Specifically, after obtaining the latitude and longitude information of the sampling points corresponding to the reverse flow terminals, the 5G network weak coverage points can be analyzed based on the latitude and longitude information of these sampling points, and the network coverage can be optimized accordingly to solve the problem of weak 5G network coverage.

[0107] The network coverage optimization method provided in the embodiment of the present application obtains the latitude and longitude information of the sampling point corresponding to the reverse flow terminal by screening and analyzing the MDT data of the reverse flow cell according to the terminal capability information and network login record information of the terminal, and thereby determines the weak coverage points of the second-standard network in the reverse flow cell without the need for on-site investigation. The method is not only efficient and low-cost, but also more accurate in determining the weak coverage points of the second-standard network.

[0108] In some embodiments, determining the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points includes:

[0109] The points corresponding to the latitude and longitude coordinates of multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the location of the newly planned second-standard network site.

[0110] Specifically, after obtaining the latitude and longitude information of the sampling points corresponding to the reverse flow terminal, it can be considered that the points corresponding to the latitude and longitude coordinates of these sampling points are the 5G network weak coverage points in the 4G reverse flow cell. Then, based on these 5G network weak coverage points, the center position of these 5G network weak coverage points can be determined. The center position can be a center position of the average center or the median center, which is not limited here.

[0111] In some embodiments, determining the center position of the weak coverage point of the second standard network includes:

[0112] The kernel density estimation algorithm is used to determine the average center point of the weak coverage points of the second standard network;

[0113] The average center point is determined as the center position of the weak coverage point of the second standard network.

[0114] Specifically, based on these 5G network weak coverage points, the machine learning kernel density estimation (KDE) algorithm can be used to determine the center position of the 5G network weak coverage point. In this embodiment, the kernel density estimation algorithm can be used to calculate the coordinates of the average center point of the 5G network weak coverage point, and the point corresponding to the coordinate is used as the center position of the 5G network weak coverage point.

[0115] Figure 3 This is an example diagram of the kernel density estimation algorithm processing process provided in the embodiment of the present application, such as Figure 3 As shown, the latitude and longitude coordinates of multiple sampling points corresponding to the reverse flow terminal are input, and the average center point coordinates of these sampling points are output using the kernel density estimation algorithm to obtain the center position of the weak coverage point of the 5G network. The specific process of calculating the average center point coordinates using the kernel density estimation algorithm can refer to the existing kernel density estimation algorithm calculation process, which will not be repeated here.

[0116] In order to better understand the technical solution of the present application, the kernel density estimation algorithm is briefly introduced below.

[0117] Kernel density estimation algorithms are often used in statistics as a method to estimate the probability density function based on a finite sample. The function of the probability density function of a random variable is to describe the characteristics of the random variable. In practical applications, the overall probability density function is usually unknown. Generally, by sampling or collecting a certain number of samples, the overall probability density can be inferred from the sample set based on statistical knowledge. This method is collectively called probability density estimation, that is, determining the probability distribution of a random variable based on training samples.

[0118] Probability density estimation methods are roughly divided into two categories: parametric estimation and nonparametric estimation. The kernel density estimation algorithm used in this application belongs to one of the nonparametric estimation methods. The selection of kernel function and bandwidth is the key to the kernel density estimation algorithm, which determines the accuracy of the center position determination.

[0119] Figure 4 The various kernel function curve examples provided in the embodiments of the present application are as follows: Figure 4As shown, the curve shape and function of each kernel function are different. Due to the convenient mathematical properties of the Gaussian kernel, the Gaussian kernel function can be used in the embodiment of the present application, that is, K(x)=φ(x), φ(x) is the standard normal probability density function, K(x) represents the kernel function, and x represents the independent variable of the kernel function.

[0120] After the kernel function is determined to use the Gaussian kernel function, different bandwidths will lead to very different final fitting results, so it is necessary to select an appropriate bandwidth. When the variance of the Gaussian kernel function, that is, h (also called bandwidth, window or neighborhood), theoretically approaches 0, the finer the sample point division, the better. However, if h is too small, there will be too few points in the neighborhood participating in the fitting, affecting the fitting results. In the kernel density estimation algorithm, the cross-validation method can be used with the help of machine learning method theory to select the optimal bandwidth h. The specific process can refer to the existing related technologies and will not be repeated here.

[0121] In some embodiments, adjusting the coverage position of an existing second-standard network site includes:

[0122] When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth coverage center position of the NR 700M site cell;

[0123] The NR2.6G site cell is a cell of the NR 2.6G site that is within the first distance range around the center position and is closest to the center position; the NR 700M site cell is a cell of the NR 700M site that is within the second distance range around the center position and is closest to the center position.

[0124] Specifically, after determining the central position of the 5G weak coverage point, network coverage optimization can be performed based on the central position. For example, the coverage direction of the existing 5G network site can be adjusted to cover the central position, or a new 5G network site can be planned at the central position.

[0125] Among them, adjusting the coverage direction of the existing 5G network site may be adjusting the coverage direction of the New Radio (NR) 2.6G site cell or the NR 700M site cell. The NR 2.6G site refers to a site in the 2.6GHz frequency band of the 5G network, and the NR 700M site refers to a site in the 700MHz frequency band of the 5G network.

[0126] For example, the cell of the NR 2.6G site closest to the center position within the first distance range around the center position of the 5G weak coverage point can be adjusted to point the beam normal of the cell to the center position.

[0127] The first distance range around the center position may be a range covered by a radius with the center position as the center and the length of the first distance. The first distance may be flexibly set and is not limited here. For example, it may be 500 meters. Then, the beam normal of the cell of the NR 2.6G site closest to the center position within a range of 500 meters around the center position may be directed to the center position.

[0128] For example, the cell of the NR 700M site closest to the center position within the second distance range around the center position of the 5G weak coverage point can be adjusted to cover the azimuth angle of the cell with the center position.

[0129] The second distance range around the center position may be a range covered by a radius with the center position as the center and the length of the second distance. The second distance may be flexibly set and is not limited here. For example, it may be 1000 meters. Then, the azimuth of the cell of the NR 700M site closest to the center position within a range of 1000 meters around the center position may cover the center position.

[0130] In some embodiments, adjusting the beam normal of a new radio interface NR 2.6G site cell to point to a center position, or adjusting the azimuth coverage center position of an NR 700M site cell includes:

[0131] If there is an NR 2.6G site within the first distance range around the center position, adjust the beam normal of the NR 2.6G site cell to point to the center position;

[0132] If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, adjust the azimuth angle of the NR 700M site cell to cover the center position.

[0133] For example, assuming that the first distance is 500 meters and the second distance is 1000 meters, if there is only an NR 2.6G site within 500 meters around the center position (there is no NR 700M site within 1000 meters), in this case, the beam normal of the NR 2.6G site cell closest to the center position can be adjusted to point to the center position; or, if there are both NR 2.6G sites within 500 meters and NR 700M sites within 1000 meters around the center position, in this case, the beam normal of the NR 2.6G site cell closest to the center position can be adjusted to point to the center position.

[0134] For another example, assuming that the first distance is 500 meters and the second distance is 1000 meters, if there is no NR 2.6G site within 500 meters around the center position, but there is an NR 700M site within 1000 meters around the center position, in this case the azimuth angle of the NR700M site cell can be adjusted to cover the center position.

[0135] In an embodiment of the present application, the beam normal refers to the center line of the fan-shaped area scanned by the beam, and the beam may be a synchronization signal block (Synchronization Signal and PBCH block, SSB) beam, a channel state information (CSI) beam or a beam covered by other signals. Figure 5 The network coverage optimization example diagram provided in the embodiment of the present application is as follows: Figure 5 As shown in the figure, before adjusting the direction of the beam normal, the beam normal of the beam emitted by the 5G site does not point to the concentrated area of ​​the reverse flow 4G MDT sampling points (i.e., the sampling points corresponding to the reverse flow terminals), and the points in these areas are the points with weak coverage of the 5G network; after adjusting the direction of the beam normal, the beam normal of the beam emitted by the 5G site points to the center of the concentrated area of ​​the reverse flow 4G MDT sampling points, thereby optimizing the network coverage and solving the problem of weak coverage of the 5G network.

[0136] In some embodiments, the beam normal may include the normal of the SSB beam and the normal of the CSI beam. For example, adjusting the beam normal of the NR 2.6G site cell closest to the center position to point to the center position of the weak coverage point of the 5G network may be adjusting the SSB beam normal and the CSI beam normal of the NR 2.6G site cell closest to the center position to point to the center position of the weak coverage point of the 5G network, so as to improve the coverage level of the area around the center position, ensure user perception, improve the 5G diversion ratio and residence ratio, and maximize the value of the 5G network.

[0137] The methods provided in the embodiments of the present application are based on the same application concept, so the implementation of each method can refer to each other, and the repeated parts will not be repeated.

[0138] The following describes the methods provided in the above embodiments of the present application by using examples of specific application scenarios.

[0139] Figure 6 The network coverage optimization method implementation flow chart provided in the embodiment of the present application is as follows: Figure 6 As shown in the figure, the implementation process mainly includes:

[0140] 1. Obtain the list of 4G high backflow cells through the platform network management.

[0141] 2. Extract the MDT data of these 4G high backflow cells.

[0142] 3. Filter the extracted 4G high backflow cell MDT data according to the terminal capability information and network login record information, filter out the sampling point information where the terminal has 5G capability and has 5G network login records, and extract the trajectory longitude and latitude of these sampling points.

[0143] 4. Use the machine learning kernel density estimation algorithm to determine the center position (average center point position) of the extracted 4G MDT sampling point trajectory longitude and latitude.

[0144] 5. Determine whether there is an NR 2.6G site within 500 meters around the center location or whether there is an NR 700M site within 1000 meters.

[0145] 6. If there is only an NR 2.6G site within 500 meters around the center, adjust the SSB beam and CSI beam of the 2.6G site cell closest to the center to cover the center; if there is only an NR 700M site within 1000 meters around the center, adjust the azimuth of the nearest 700M site cell to cover the center; if there is both an NR 2.6G site within 500 meters and an NR 700M site within 1000 meters around the center, only adjust the SSB beam and CSI beam normal of the 2.6G site cell closest to the center to cover the center; if there is no NR 2.6G site within 500 meters around the center and no NR 700M site within 1000 meters, plan a new site at the center.

[0146] 7. End.

[0147] The network coverage optimization method provided in the embodiment of the present application has high efficiency in backflow ratio analysis, and does not require on-site survey. The distribution area of ​​backflow users can be determined through MDT data and terminal capability information; the accuracy of backflow area judgment is high. Compared with the traditional on-site survey that determines the distribution area of ​​backflow users by crowd density, the method provided in the present application determines the distribution area of ​​backflow users by combining MDT data and capability information data reported by the terminal, and the judgment is more accurate; the user distribution density is calculated by the latitude and longitude trajectory of the backflow users through the machine learning kernel density estimation algorithm to determine the center position of the weak coverage point, which is more reasonable than the traditional method; the coverage is improved by adjusting the SSB beam and the CSI beam, and there is no need to adjust the antenna on the site, saving costs.

[0148] The methods and devices provided in the various embodiments of the present application are based on the same application concept. Since the methods and devices solve problems based on similar principles, the implementation of the devices and methods can refer to each other, and the repeated parts will not be repeated.

[0149] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Figure 7 As shown, the electronic device includes a memory 720, a transceiver 710 and a processor 700; wherein the processor 700 and the memory 720 may also be arranged physically separately.

[0150] The memory 720 is used to store computer programs; the transceiver 710 is used to send and receive data under the control of the processor 700.

[0151] Specifically, the transceiver 710 is used to receive and send data under the control of the processor 700 .

[0152] Among them, Figure 7 In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 700 and memory represented by memory 720. The bus architecture may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described in this application. The bus interface provides an interface. The transceiver 710 may be a plurality of components, namely, a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, which may include a wireless channel, a wired channel, an optical cable, and other transmission media.

[0153] The processor 700 is responsible for managing the bus architecture and general processing, and the memory 720 can store data used by the processor 700 when performing operations.

[0154] The processor 700 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or a complex programmable logic device (CPLD). The processor may also adopt a multi-core architecture.

[0155] The processor 700 calls the computer program stored in the memory 720 to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions, for example: obtaining the minimized drive test (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; the reverse flow cell is a cell of the first standard network; according to the terminal capability information and the terminal login record information, the MDT data of the reverse flow cell is screened, and the longitude and latitude information of multiple sampling points corresponding to the reverse flow terminal is obtained from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the standard of the second standard network is higher than that of the first standard network; according to the longitude and latitude information of the multiple sampling points, the second standard network weak coverage point in the reverse flow cell is determined, and the second standard network weak coverage point is used for network coverage optimization.

[0156] In some embodiments, the MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, including:

[0157] According to the terminal capability information and the terminal login record information, the reverse flow terminal is screened out from the terminals in the reverse flow cell;

[0158] The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

[0159] In some embodiments, determining the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points includes:

[0160] The points corresponding to the latitude and longitude coordinates of multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the location of the newly planned second-standard network site.

[0161] In some embodiments, determining the center position of the weak coverage point of the second standard network includes:

[0162] The kernel density estimation algorithm is used to determine the average center point of the weak coverage points of the second standard network;

[0163] The average center point is determined as the center position of the weak coverage point of the second standard network.

[0164] In some embodiments, the kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

[0165] In some embodiments, the first standard network is a 4G network, and the second standard network is a 5G network.

[0166] In some embodiments, adjusting the coverage position of an existing second-standard network site includes:

[0167] When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth coverage center position of the NR 700M site cell;

[0168] The NR2.6G site cell is a cell of the NR 2.6G site that is within the first distance range around the center position and is closest to the center position; the NR 700M site cell is a cell of the NR 700M site that is within the second distance range around the center position and is closest to the center position.

[0169] In some embodiments, adjusting the beam normal of a new radio interface NR 2.6G site cell to point to a center position, or adjusting the azimuth coverage center position of an NR 700M site cell includes:

[0170] If there is an NR 2.6G site within the first distance range around the center position, adjust the beam normal of the NR 2.6G site cell to point to the center position;

[0171] If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, adjust the azimuth angle of the NR 700M site cell to cover the center position.

[0172] In some embodiments, the beam normal includes a normal of a synchronization signal block (SSB) beam and a normal of a channel state information (CSI) beam.

[0173] It should be noted here that the above-mentioned electronic device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0174] Figure 8 A schematic diagram of the structure of the network coverage optimization device provided in the embodiment of the present application is shown in FIG. Figure 8 As shown, the device comprises:

[0175] The acquisition unit 800 is used to acquire the minimization of drive test (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; the reverse flow cell is a cell of the first standard network;

[0176] The screening unit 810 is used to screen the MDT data of the reverse flow cell according to the terminal capability information and the terminal login record information, and obtain the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network;

[0177] The determination unit 820 is used to determine the second standard network weak coverage point position in the reverse flow cell according to the latitude and longitude information of multiple sampling points, and the second standard network weak coverage point position is used for network coverage optimization.

[0178] In some embodiments, the MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, including:

[0179] According to the terminal capability information and the terminal login record information, the reverse flow terminal is screened out from the terminals in the reverse flow cell;

[0180] The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

[0181] In some embodiments, determining the second standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of multiple sampling points includes:

[0182] The points corresponding to the latitude and longitude coordinates of multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the location of the newly planned second-standard network site.

[0183] In some embodiments, determining the center position of the weak coverage point of the second standard network includes:

[0184] The kernel density estimation algorithm is used to determine the average center point of the weak coverage points of the second standard network;

[0185] The average center point is determined as the center position of the weak coverage point of the second standard network.

[0186] In some embodiments, the kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

[0187] In some embodiments, the first standard network is a 4G network, and the second standard network is a 5G network.

[0188] In some embodiments, adjusting the coverage position of an existing second-standard network site includes:

[0189] When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth coverage center position of the NR 700M site cell;

[0190] The NR2.6G site cell is a cell of the NR 2.6G site that is within the first distance range around the center position and is closest to the center position; the NR 700M site cell is a cell of the NR 700M site that is within the second distance range around the center position and is closest to the center position.

[0191] In some embodiments, adjusting the beam normal of a new radio interface NR 2.6G site cell to point to a center position, or adjusting the azimuth coverage center position of an NR 700M site cell includes:

[0192] If there is an NR 2.6G site within the first distance range around the center position, adjust the beam normal of the NR 2.6G site cell to point to the center position;

[0193] If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, adjust the azimuth angle of the NR 700M site cell to cover the center position.

[0194] In some embodiments, the beam normal includes a normal of a synchronization signal block (SSB) beam and a normal of a channel state information (CSI) beam.

[0195] It should be noted that the division of units in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0196] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application is essentially 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, 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, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program code.

[0197] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0198] On the other hand, an embodiment of the present application further provides a non-transitory readable storage medium, wherein the non-transitory readable storage medium stores a computer program, and the computer program is used to enable a processor to execute the network coverage optimization method provided in the above embodiments.

[0199] It should be noted here that the non-transitory readable storage medium provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0200] The non-transitory readable storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.

[0201] The technical solution provided in the embodiment of the present application can be applicable to a variety of systems, especially 5G systems. For example, the applicable system can be a global system of mobilecommunication (GSM) system, a code division multiple access (CDMA) system, a wideband code division multiple access (WCDMA) general packet radio service (GPRS) system, a long term evolution (LTE) system, a LTE frequency division duplex (FDD) system, a LTE time division duplex (TDD) system, an advanced long term evolution (LTE-A) system, a universal mobiletelecommunicationsystem (UMTS), a world-wide interoperabilityformicrowave access (WiMAX) system, a 5G new air interface (NR) system, etc. These various systems include terminal equipment and network equipment. The system may also include a core network part, such as an evolved packet system (EPS), a 5G system (5GS), etc.

[0202] The terminal involved in the embodiment of the present application may be a device that provides voice and / or data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem. In different systems, the name of the terminal may also be different. For example, in a 5G system, the terminal may be called a user equipment (UE). A wireless terminal device can communicate with one or more core networks (CN) via a radio access network (RAN). The wireless terminal device may be a mobile terminal device, such as a mobile phone (or a "cellular" phone) and a computer with a mobile terminal device. For example, it may be a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device that exchanges language and / or data with a wireless access network. For example, personal communication service (PCS) phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs) and other devices. The wireless terminal device may also be referred to as a system, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, an access point, a remote terminal device, an access terminal device, a user terminal, a user agent, and a user device, but is not limited thereto in the embodiments of the present application.

[0203] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0204] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer executable instructions. These computer executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0205] These processor executable instructions may also be stored in a processor readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0206] These processor-executable instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0207] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A network coverage optimization method, characterized in that: include: Acquire the Minimization of Drive Tests (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; The reverse flow cell is a cell of the first standard network; The MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, and the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal is obtained from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network; According to the latitude and longitude information of the multiple sampling points, the second-standard network weak coverage point in the reverse flow cell is determined, and the second-standard network weak coverage point is used for network coverage optimization.

2. The network coverage optimization method according to claim 1, characterized in that: The screening of the MDT data of the reverse flow cell according to the terminal capability information and the terminal login record information includes: Filtering the reverse flow terminal from the terminals in the reverse flow cell according to the terminal capability information and the terminal login record information; The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

3. The network coverage optimization method according to claim 1, characterized in that: The determining, according to the latitude and longitude information of the plurality of sampling points, the second standard network weak coverage point in the reverse flow cell comprises: The points corresponding to the latitude and longitude coordinates of the multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the position of the newly planned second-standard network site.

4. The network coverage optimization method according to claim 3, characterized in that: The determining the central position of the weak coverage point of the second standard network includes: Determine the average center point of the weak coverage points of the second standard network by using a kernel density estimation algorithm; The average center point is determined as the center position of the weak coverage point of the second-standard network.

5. The network coverage optimization method according to claim 4, characterized in that: The kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

6. The network coverage optimization method according to any one of claims 1 to 5, characterized in that: The first-standard network is a 4G network, and the second-standard network is a 5G network.

7. The network coverage optimization method according to any one of claims 3 to 5, characterized in that: The adjusting the coverage position of the existing second-standard network site includes: When the second standard network is a 5G network, adjust the beam normal of the new air interface NR 2.6G site cell to point to the center position, or adjust the azimuth angle of the NR 700M site cell to cover the center position; The NR 2.6G site cell is a cell of the NR 2.6G site closest to the center position within a first distance range around the center position; the NR 700M site cell is a cell of the NR 700M site closest to the center position within a second distance range around the center position.

8. The network coverage optimization method according to claim 7, characterized in that: The adjusting the beam normal of the new radio interface NR 2.6G site cell to point to the center position, or adjusting the azimuth angle of the NR 700M site cell to cover the center position, includes: If there is an NR 2.6G site within a first distance range around the center position, adjusting the beam normal of the NR 2.6G site cell to point to the center position; If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, the azimuth angle of the NR 700M site cell is adjusted to cover the center position.

9. The network coverage optimization method according to claim 7, characterized in that: The beam normal includes the normal of the synchronization signal block SSB beam and the normal of the channel state information CSI beam.

10. An electronic device, characterized in that: Including memory, transceiver, processor; A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations: Acquire the Minimization of Drive Tests (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; the reverse flow cell is a cell of the first standard network; The MDT data of the reverse flow cell is screened according to the terminal capability information and the terminal login record information, and the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal is obtained from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network; According to the latitude and longitude information of the multiple sampling points, the second-standard network weak coverage point in the reverse flow cell is determined, and the second-standard network weak coverage point is used for network coverage optimization.

11. The electronic device according to claim 10, characterized in that: The screening of the MDT data of the reverse flow cell according to the terminal capability information and the terminal login record information includes: Filtering the reverse flow terminal from the terminals in the reverse flow cell according to the terminal capability information and the terminal login record information; The MDT data corresponding to the reverse flow terminal is filtered out from the MDT data of the reverse flow cell.

12. The electronic device according to claim 10, characterized in that: The determining, according to the latitude and longitude information of the plurality of sampling points, the second standard network weak coverage point in the reverse flow cell comprises: The points corresponding to the latitude and longitude coordinates of the multiple sampling points are used as the weak coverage points of the second-standard network in the reverse flow cell, and the center position of the weak coverage points of the second-standard network is determined. The center position is used to adjust the coverage orientation of the existing second-standard network site, or to determine the position of the newly planned second-standard network site.

13. The electronic device according to claim 12, characterized in that: The determining the central position of the weak coverage point of the second standard network includes: Determine the average center point of the weak coverage points of the second standard network by using a kernel density estimation algorithm; The average center point is determined as the center position of the weak coverage point of the second-standard network.

14. The electronic device according to claim 13, characterized in that: The kernel function of the kernel density estimation algorithm is a Gaussian kernel function.

15. The electronic device according to any one of claims 10 to 14, characterized in that: The first-standard network is a 4G network, and the second-standard network is a 5G network.

16. The electronic device according to any one of claims 12 to 14, characterized in that: The adjusting the coverage position of the existing second-standard network site includes: When the second standard network is a 5G network, adjust the beam normal of the new air interface NR2.6G site cell to point to the center position, or adjust the azimuth angle of the NR700M site cell to cover the center position; The NR 2.6G site cell is a cell of the NR 2.6G site closest to the center position within a first distance range around the center position; the NR 700M site cell is a cell of the NR 700M site closest to the center position within a second distance range around the center position.

17. The electronic device according to claim 16, characterized in that: The adjusting the beam normal of the new radio interface NR 2.6G site cell to point to the center position, or adjusting the azimuth angle of the NR 700M site cell to cover the center position, includes: If there is an NR 2.6G site within a first distance range around the center position, adjusting the beam normal of the NR 2.6G site cell to point to the center position; If there is no NR 2.6G site within the first distance range around the center position, but there is an NR 700M site within the second distance range around the center position, the azimuth angle of the NR 700M site cell is adjusted to cover the center position.

18. The electronic device according to claim 16, characterized in that: The beam normal includes the normal of the synchronization signal block SSB beam and the normal of the channel state information CSI beam.

19. A network coverage optimization device, characterized in that: include: An acquisition unit, configured to acquire the Minimization of Drive Tests (MDT) data of the reverse flow cell and the terminal capability information of the terminal in the reverse flow cell; The reverse flow cell is a cell of the first standard network; a screening unit, configured to screen the MDT data of the reverse flow cell according to the terminal capability information and the terminal login record information, and obtain the latitude and longitude information of multiple sampling points corresponding to the reverse flow terminal from the screened MDT data; the reverse flow terminal is a terminal in the reverse flow cell that supports the second standard network and has a second standard network login record, and the second standard network is higher than the first standard network; A determination unit is used to determine the second-standard network weak coverage point in the reverse flow cell according to the latitude and longitude information of the multiple sampling points, and the second-standard network weak coverage point is used for network coverage optimization.

20. A non-transitory readable storage medium, characterized in that: The non-transitory readable storage medium stores a computer program, and the computer program is used to enable a processor to execute the method according to any one of claims 1 to 9.

Images