A network configuration method and device

Abstract

The embodiment of the present application discloses a network configuration method and device, which can be executed by an offline tool deployed offline on a stand-alone computer or on the cloud, or by an online tool deployed online to a network management system OMC or an online tool platform connected to the OMC. The method can construct a three-dimensional grid based on the average RSRP of each cell in the MR data and the horizontal beam information and vertical beam information corresponding to the main beam identifier of each cell, thereby achieving the goal of constructing a three-dimensional grid without relying on MDT data. In addition, a path loss matrix can be constructed based on the three-dimensional grid to achieve three-dimensional beam optimization. The method can also determine the network configuration parameters of the target cell based on the path loss matrix, which is conducive to optimizing the coverage and / or capacity of the network.

Description

Technical Field

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

[0002] In wireless communication networks, sites are usually deployed in a cellular shape, and the coverage of each site is determined by the radio frequency parameters. Among them, coverage is an important indicator for measuring the performance of wireless networks. In order to quantify the coverage performance indicators of wireless networks, the coverage area of ​​one or more cells can be modeled in a two-dimensional plane rasterization manner to optimize the coverage performance indicators. However, two-dimensional plane rasterization modeling requires projecting the vertical surface features in the three-dimensional coverage onto a two-dimensional plane, which loses the vertical surface coverage features, resulting in poor vertical surface coverage signals, leading to problems such as weak coverage and overlapping coverage. Summary of the invention

[0003] An embodiment of the present application provides a network configuration method, which can construct three-dimensional coverage features based on measurement report MR data, which is conducive to optimizing three-dimensional coverage.

[0004] In the first aspect, an embodiment of the present application provides a network configuration method, which can be executed by a network management device, and the network management device can be deployed offline on a stand-alone computer or a cloud (i.e., an offline tool), or can be deployed online on a network management system OMC or an online tool platform connected to the OMC (i.e., an online tool). Among them, the network management device can aggregate multiple MR data according to the cell information of each MR in multiple measurement report MR data to obtain N groups of MR data, and obtain the average reference signal received power RSRP of each cell of each group of MR in the N groups of MR. For each group of MRs in the N groups of MRs, the network management device creates a three-dimensional grid of the group of MRs based on the average RSRP of each cell in the group of MRs and the vertical beam range and horizontal beam range corresponding to the main beam identifier of each cell. For the three-dimensional grid of each group of MRs, the path loss between the main beam of each cell in the group of MRs to the three-dimensional grid is calculated to obtain the path loss matrix of the three-dimensional grid. Finally, the network management device can determine the network configuration parameters of the target cell according to the path loss matrix of the N three-dimensional grids. The target cell is a cell whose coverage index does not meet the preset coverage index and / or capacity index does not meet the preset capacity index.

[0005] It can be seen that the network management device can construct a three-dimensional grid based on the average RSRP of each cell in the MR data and the horizontal beam information and vertical beam information corresponding to the main beam identifier of each cell, thereby achieving the goal of constructing a three-dimensional grid without relying on MDT data. In addition, a three-dimensional path loss matrix can be constructed based on the three-dimensional grid to achieve three-dimensional beam optimization. The network management device can also determine the network configuration parameters of the target cell based on the three-dimensional path loss matrix, which is conducive to optimizing the coverage and / or capacity of the network.

[0006] In one possible design, the cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell, wherein the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. Before aggregating the multiple MR data according to the cell information of each MR in the multiple measurement report MR data, the network management device can determine the main beam prediction model of the serving cell of each MR according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MR. Then, the main beam identifier of the neighboring cell of the MR is determined according to the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell.

[0007] It can be seen that the network management device can predict the main beam identifier of MR in its service cell and each neighboring cell, thereby obtaining the full main beam properties of MR, which is beneficial for the network management device to consider the overall network performance when performing coverage and / or capacity optimization.

[0008] In a possible design, when the network management device aggregates the MR data, it can aggregate the MR data with the same cell identifier, the same main beam identifier, and the level difference satisfying the preset level difference condition to determine a group of aggregated MRs. The level difference is the difference in RSRP between two cells with the same cell identifier and the same main beam identifier in the MR data.

[0009] It can be seen that the MR data collected by the network management device is MR data with similar wireless space propagation, which is conducive to modeling a three-dimensional grid at a specified location. In addition, according to the cell attributes, RSRP, beam attributes, etc. of MR, similar feature MRs are aggregated and processed, which is conducive to more precise simulation of actual network propagation and greatly reducing the amount of calculation.

[0010] In a possible design, for each group of MR three-dimensional grids, the network management device can obtain the beam gain corresponding to the main beam identifier of any cell i in the group of MRs according to the main beam identifier of the cell i; the beam gain of the cell i is determined according to the horizontal beam range, vertical beam range, antenna gain, signal attenuation value corresponding to the horizontal beam range, and signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i. The network management device then calculates the path loss from the main beam of the cell i to the three-dimensional grid of the group of MRs according to the transmit power of the cell i, the beam gain of the cell i, and the average RSRP of the cell i.

[0011] It can be seen that when calculating the path loss of the three-dimensional grid of each group of MRs, the network management device fully considers the average RSRP of the horizontal beam, vertical beam and cell. That is to say, the calculated path loss reflects the path loss of the three-dimensional grid, avoiding the loss of coverage and capacity characteristics caused by the average processing of the two-dimensional geographic grid.

[0012] In one possible design, the network management device determines the target cell of each three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid. According to the preset coverage index and preset capacity index of the target cell, the network configuration parameters of the target cell are adjusted. According to the adjusted network configuration parameters of the target cell, the adjusted antenna gain of the target cell is obtained; the coverage index and capacity index of the target cell are determined according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell. If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

[0013] It can be seen that the network management device can screen out target cells with coverage problems and / or capacity problems, and optimize the coverage and / or capacity of the target cells by adjusting the network configuration parameters of the target cells.

[0014] In one possible design, the network configuration parameters include one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0015] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0016] In a second aspect, an embodiment of the present application provides a network configuration method, which can be executed by a network management device. Among them, the network management device can aggregate multiple MDT data according to the cell information of each MDT in multiple minimized road test MDT data to obtain N groups of MDT data, and each group of MDT includes MDTs with the same vertical beam identifier of the cell. For each group of MDTs in the N groups of MDTs, a three-dimensional grid of the group of MDTs is created according to the longitude, latitude and vertical beam identifier of each cell in the group of MDTs. For the three-dimensional grid of each group of MDTs, the path loss between the main beam of each cell in the group of MDTs and the three-dimensional grid is calculated to obtain the path loss matrix of the three-dimensional grid. According to the path loss matrices of N three-dimensional grids, the network configuration parameters of the target cell are determined, wherein the target cell is a cell whose coverage index does not meet the preset coverage index and / or whose capacity index does not meet the preset capacity index.

[0017] It can be seen that the network management device can construct a three-dimensional grid based on the latitude and longitude information in the MDT data and the vertical beam identifier determined according to the main beam identifier of the cell, so as to avoid the averaging of the data by the two-dimensional geographic grid, which blurs the three-dimensional information and is conducive to achieving more accurate three-dimensional optimization. In addition, the network management device can generate a three-dimensional path loss matrix based on the three-dimensional grid, and the network configuration parameters of the target cell can be determined based on the three-dimensional path loss matrix, which is conducive to optimizing the coverage and / or capacity of the network.

[0018] In one possible design, for each MDT, the network management device determines the main beam prediction model of the service cell of the MDT according to the cell identifier of the service cell, the RSRP of the service cell, and the main beam identifier of the service cell in the MDT. The main beam identifier of the neighboring cell of the MDT is determined according to the main beam prediction model of the service cell of the MDT, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell. The vertical beam identifier of each cell in the MDT is determined according to the main beam identifier of each cell in the MDT.

[0019] It can be seen that the network management device can determine the vertical beam identifier of each cell in the MDT data, thereby marking each cell in the MDT data on a three-dimensional level and determining the three-dimensional information of each cell.

[0020] In one possible design, the network management device determines the grid longitude and grid latitude of the plane grid formed by the group of MDTs based on the longitude and latitude of each cell in the group of MDTs; and then determines the vertical layer of the plane grid formed by the group of MDTs based on the vertical beam identifier of the group of MDTs to obtain the three-dimensional grid of the group of MDTs.

[0021] It can be seen that the network management device can determine a two-dimensional plane grid according to the latitude and longitude information in the MDT data, and then determine the three-dimensional position of the plane grid according to the vertical beam identifier, thereby constructing a three-dimensional grid.

[0022] In a possible design, the network management device obtains the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs according to the vertical beam identifier in the group of MDTs. According to the grid longitude and grid latitude of the group of MDTs, the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs are obtained. According to the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs, the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs is calculated. According to the transmit power of cell i, the antenna gain from cell i to the three-dimensional grid of the group of MDTs, and the average RSRP of cell i, the path loss from cell i to the three-dimensional grid of the group of MDTs is calculated.

[0023] It can be seen that when calculating the path loss of the three-dimensional grid of each group of MDT, the network management device fully considers the average RSRP of the horizontal beam, vertical beam and cell. That is to say, the calculated path loss reflects the path loss of the three-dimensional grid, avoiding the loss of coverage and capacity characteristics caused by the average processing of the two-dimensional geographic grid.

[0024] In one possible design, the network management device determines the target cell of each three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid. Then, according to the preset coverage index and preset capacity index of the target cell, the network configuration parameters of the target cell are adjusted. According to the adjusted network configuration parameters of the target cell, the adjusted antenna gain of the target cell is obtained. According to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell, the coverage index and capacity index of the target cell are determined. If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined to be the network configuration parameters of the target cell.

[0025] It can be seen that the network management device can screen out target cells with coverage problems and / or capacity problems, and optimize the coverage and / or capacity of the target cells by adjusting the network configuration parameters of the target cells.

[0026] In one possible design, the network configuration parameters include one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0027] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0028] In a third aspect, an embodiment of the present application provides a network management device, which includes a convergence unit, an acquisition unit, a creation unit, a calculation unit, and a determination unit. The convergence unit is used to aggregate the multiple MR data according to the cell information of each MR in the multiple measurement report MR data to obtain N groups of MR data, and each group of MR includes MRs with wireless space propagation similarity. The acquisition unit is used to obtain the average reference signal received power RSRP of each cell of each group of MR in the N groups of MR. The creation unit is used to create a three-dimensional grid of the group of MRs for each group of MRs in the N groups of MRs according to the average RSRP of each cell in the group of MRs and the vertical beam range and horizontal beam range corresponding to the main beam identifier of each cell. The calculation unit is used to calculate the path loss between the main beam of each cell in the group of MRs and the three-dimensional grid for each group of MRs to obtain the path loss matrix of the three-dimensional grid. The determination unit is used to determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet the preset coverage index and / or whose capacity index does not meet the preset capacity index.

[0029] In one possible design, the cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. The determination unit is also used to determine, for each of the MRs, a main beam prediction model of the serving cell of the MR based on the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MR. The main beam identifier of the neighboring cell of the MR is determined based on the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell.

[0030] In one possible design, the aggregation unit is used to aggregate MR data with the same cell identifier, the same main beam identifier, and a level difference that satisfies a preset level difference condition, to determine a group of aggregated MRs; wherein the level difference is the difference in RSRP between each pair of cells with the same cell identifier and the same main beam identifier in the MR data.

[0031] In one possible design, the calculation unit is used to obtain the beam gain corresponding to the main beam identifier of any cell i in the group of MRs according to the main beam identifier of the cell i; the beam gain of the cell i is determined according to the horizontal beam range, vertical beam range, antenna gain, signal attenuation value corresponding to the horizontal beam range and signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i; the path loss from the main beam of the cell i to the three-dimensional grid of the group of MRs is calculated according to the transmit power of the cell i, the beam gain of the cell i and the average RSRP of the cell i.

[0032] In one possible design, for each three-dimensional grid, a determination unit is used to determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid. According to the preset coverage index and preset capacity index of the target cell, the network configuration parameters of the target cell are adjusted; according to the adjusted network configuration parameters of the target cell, the adjusted antenna gain of the target cell is obtained; according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell, the coverage index and capacity index of the target cell are determined. If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

[0033] In one possible design, the network configuration parameters include one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0034] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0035] In a fourth aspect, an embodiment of the present application provides a network management device, which includes a convergence unit, a creation unit, a calculation unit, and a determination unit. The convergence unit is used to perform convergence processing on multiple MDT data according to the cell information of each MDT in multiple minimized road test MDT data to obtain N groups of MDT data, and each group of MDT includes an MDT with the same vertical beam identifier of the cell. The creation unit is used to create a three-dimensional grid of the group of MDTs for each group of MDTs in the N groups of MDTs according to the longitude, latitude of each cell in the group of MDTs and the vertical beam identifier of each cell. The calculation unit is used to calculate the path loss between the main beam of each cell in the group of MDTs and the three-dimensional grid for each group of MDTs to obtain the path loss matrix of the three-dimensional grid. The determination unit is used to determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet the preset coverage index and / or whose capacity index does not meet the preset capacity index.

[0036] In one possible design, the cell information of each MDT includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. For each MDT, the determination unit is also used to determine the main beam prediction model of the serving cell of the MDT according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MDT. The main beam identifier of the neighboring cell of the MDT is determined according to the main beam prediction model of the serving cell of the MDT, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell; the vertical beam identifier of each cell in the MDT is determined according to the main beam identifier of each cell in the MDT.

[0037] In one possible design, a creation unit is used to determine the grid longitude and grid latitude of the plane grid formed by the group of MDTs based on the longitude and latitude of each cell in the group of MDTs; and to determine the vertical layer of the plane grid formed by the group of MDTs based on the vertical beam identifier of the group of MDTs to obtain a three-dimensional grid of the group of MDTs.

[0038] In a possible design, the calculation unit is used to obtain the vertical beam range, antenna gain and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs according to the vertical beam identifier. According to the grid longitude and grid latitude of the group of MDTs, the horizontal beam range, antenna gain and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs are obtained. According to the vertical beam range, antenna gain and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs, the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs is calculated. According to the transmit power of the cell i, the antenna gain from the cell i to the three-dimensional grid of the group of MDTs and the average RSRP of the cell i, the path loss from the cell i to the three-dimensional grid of the group of MDTs is calculated.

[0039] In one possible design, for each three-dimensional grid, a determination unit is used to determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid. According to the preset coverage index and preset capacity index of the target cell, the network configuration parameters of the target cell are adjusted; according to the adjusted network configuration parameters of the target cell, the adjusted antenna gain of the target cell is obtained. According to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell, the coverage index and capacity index of the target cell are determined. If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined to be the network configuration parameters of the target cell.

[0040] In a fifth aspect, an embodiment of the present application provides a network device, which has the function of implementing the network configuration method provided in the first aspect. The function can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

[0041] In a sixth aspect, an embodiment of the present application provides a network device having the function of implementing the network configuration method provided in the second aspect. The function can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

[0042] In the seventh aspect, an embodiment of the present application provides a computer-readable storage medium, which includes a program or instructions. When the program or instructions are run on a computer, the computer executes the method in the first aspect or any possible implementation of the first aspect.

[0043] In an eighth aspect, an embodiment of the present application provides a computer-readable storage medium, which includes a program or instructions. When the program or instructions are run on a computer, the computer executes the method in the second aspect or any possible implementation of the second aspect.

[0044] In the ninth aspect, an embodiment of the present application provides a chip or a chip system, which includes at least one processor and an interface, the interface and at least one processor are interconnected by lines, and the at least one processor is used to run computer programs or instructions to perform the method described in the first aspect or any possible implementation of the first aspect.

[0045] In the tenth aspect, an embodiment of the present application provides a chip or a chip system, which includes at least one processor and an interface, the interface and at least one processor are interconnected by lines, and the at least one processor is used to run computer programs or instructions to perform the method described in the second aspect or any possible implementation of the second aspect.

[0046] The interface in the chip may be an input / output interface, a pin or a circuit, etc.

[0047] The chip system in the above aspects may be a system on chip (SOC) or a baseband chip, etc., wherein the baseband chip may include a processor, a channel encoder, a digital signal processor, a modem and an interface module, etc.

[0048] In a possible implementation, the chip or chip system described above in the present application further includes at least one memory, in which instructions are stored. The memory may be a storage unit inside the chip, such as a register, a cache, etc., or a storage unit of the chip (e.g., a read-only memory, a random access memory, etc.).

[0049] In the eleventh aspect, an embodiment of the present application provides a computer program or a computer program product, including codes or instructions, which, when executed on a computer, enable the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0050] In the twelfth aspect, an embodiment of the present application provides a computer program or a computer program product, including codes or instructions. When the codes or instructions are executed on a computer, the computer executes the method in the second aspect or any possible implementation of the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of a wireless network provided in an embodiment of the present application;

[0052] Figure 2 A schematic diagram of network coverage and capacity provided in an embodiment of the present application;

[0053] Figure 3 A schematic diagram of a common antenna and a Massive MIMO antenna;

[0054] Figure 4 It is a schematic diagram of a two-dimensional plane grid path loss matrix;

[0055] Figure 5 A schematic diagram of a communication system provided in an embodiment of the present application;

[0056] Figure 6 A schematic diagram of beam coverage of a Massive MIMO antenna provided in an embodiment of the present application;

[0057] Figure 7 A flowchart of a network configuration method provided in an embodiment of the present application;

[0058] Figure 8 A schematic diagram of multiple beams transmitted by a Massive MIMO antenna and a main beam received by a terminal device provided in an embodiment of the present application;

[0059] Figure 9a A schematic diagram of a three-dimensional grid provided in an embodiment of the present application;

[0060] Figure 9b A schematic diagram of a path loss matrix provided in an embodiment of the present application;

[0061] Fig.10 A schematic diagram of a network optimization target optimization process provided in an embodiment of the present application;

[0062] Fig.11 A flowchart of another network configuration method provided in an embodiment of the present application;

[0063] Fig.12 A schematic diagram of an area formed by projecting a vertical layer onto the ground provided in an embodiment of the present application;

[0064] Fig.13a A schematic diagram of another three-dimensional grid provided in an embodiment of the present application;

[0065] Fig.13b A schematic diagram of another path loss matrix provided in an embodiment of the present application;

[0066] Fig.14 A schematic diagram of a network management device provided in an embodiment of the present application;

[0067] Fig.15 A schematic diagram of a network management device provided in an embodiment of the present application;

[0068] Fig.16 A schematic diagram of another network management device provided in an embodiment of the present application;

[0069] Fig.17 A schematic diagram of another network management device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0071] Wireless communication networks deploy sites in a cellular shape. The coverage of each site is determined by its radio frequency parameters. Coverage determines the strength of the wireless signal received by users, which affects the number of users (capacity) that can be connected to the site. Figure 1 , Figure 1 A schematic diagram of a wireless network provided in an embodiment of the present application. The wireless network includes multiple sites, each of which is deployed according to a certain spatial distribution, such as Figure 1 As shown in Figure 1. The coverage area of ​​a site (also called a cell) is as follows: Figure 1 The dotted area shown in the figure is the coverage area composed of multiple sites. Figure 1 shown.

[0072] Coverage and capacity are important indicators for measuring the performance of wireless networks. However, due to differences between network planning and the actual physical environment, changes in urban construction, user development, etc., wireless networks may have coverage problems such as weak coverage and overlapping coverage, as well as capacity problems such as load imbalance and hotspot traffic suppression. Figure 2 shown.

[0073] Among them, weak coverage means that the average reference signal received power (RSRP) in the current area is lower than a certain threshold. For example, Figure 2 The weak coverage area in the figure is located between cell 1 and cell 2, and is located at the edge of cell 1 and cell 2. Users in this weak coverage area may not be able to receive signals normally. Overlapping coverage refers to the overlapping area between adjacent cells, for example, Figure 2 The shaded area between cells 2 and 3 in the figure. Hotspot traffic suppression means that the signal quality in the current area is poor and more energy is required to send data. For example, Figure 2 There are a large number of access users in the hotspot coverage area of ​​cell 1, and there is a problem of hotspot traffic suppression.

[0074] In order to ensure that users can have a better experience (for example, to ensure a higher network speed), the wireless network must have a better reception level, less interference, and a more balanced user distribution. In other words, the wireless network needs to consider both coverage and capacity, two important performance indicators. In order to achieve the coverage and capacity indicators of the wireless network, the coverage and capacity of the site can be controlled by adjusting the RF parameters of the antenna.

[0075] Common antennas may include single input single output (SISO) and multiple input multiple output (MIMO). For example, common antennas may include 2TRx, 4TRx or 8TRx, such as Figure 3 As shown in Figure 2, with the evolution of communication technology, Massive MIMO has emerged. Massive MIMO is the fifth generation of mobile communications (the 5 th Massive MIMO antennas integrate more antennas to achieve three-dimensional precise beamforming and multi-user beam multiplexing, thereby achieving better coverage and greater capacity. Common Massive MIMO antennas include 32TRx and 64TRx, such as Figure 3 shown.

[0076] After the introduction of Massive MIMO technology, broadcast beam weights for different coverage scenarios are provided, so that the RF parameters are changed from 3 types of ordinary antennas (physical azimuth, physical downtilt, digital downtilt) to 6 types of Massive MIMO antennas (physical azimuth, physical downtilt, digital azimuth, digital downtilt, horizontal beam width, vertical beam width). In addition, in the 5G system, in addition to adjusting the shape of the horizontal envelope and vertical envelope of the beam as a whole, the beam of the broadcast beam can also be adjusted independently to form coverage of any shape. In other words, by adjusting the RF parameters of the MIMO antenna, the coverage rate of the cell can be improved.

[0077] The existing method for adjusting the RF parameters of MIMO antennas is usually to perform geographic grid modeling on the coverage optimization area based on the minimization of drive tests (MDT) data reported by the terminal equipment, and obtain a two-dimensional plane grid path loss matrix, such as Figure 4 As shown in the figure, the optimization target is the coverage index. Based on the two-dimensional grid-level path loss matrix and the optimization target, the RF parameters are derived, and the RF parameters are adjusted according to the derivatives of the RF parameters to improve the cell coverage.

[0078] However, Massive MIMO antennas enhance three-dimensional coverage compared to ordinary antennas. Two-dimensional gridding projects vertical features directly onto a two-dimensional plane and averages the data in the same grid, which loses vertical coverage features and leads to poor vertical coverage signals in buildings. In addition, in scenarios with low MDT terminal penetration (e.g. Figure 4As shown in the shaded area, due to the lack of MDT data in this scenario, the above adjustment method cannot be used to perform geographic grid modeling of the coverage area, and coverage optimization cannot be performed.

[0079] In order to solve the above problems, an embodiment of the present application provides a network configuration method, which can construct three-dimensional coverage features based on measurement report MR data and model a path loss matrix, thereby facilitating the optimization of three-dimensional coverage.

[0080] This network configuration method can be deployed offline on a stand-alone personal computer (PC) or in the cloud (offline tool), or online on an operation maintenance center (OMC) or an online tool platform connected to the OMC (online tool). Figure 5 , Figure 5 A communication system is provided in an embodiment of the present application, and the communication system includes an OMC, a network device, and a terminal device. In particular, the present application embodiment is described by taking an online tool deployed to connect to the OMC as an example. The OMC can communicate with each network device and can also communicate with the online tool Online Tool, such as Figure 5 shown.

[0081] Among them, OMC can obtain data reported by terminal devices and network devices.

[0082] To facilitate understanding of the embodiments of the present application, the technical terms involved in the embodiments of the present application are described below.

[0083] Massive multiple input multiple output (MassiveMIMO) is a fifth generation mobile communication technology. th Massive MIMO antennas integrate more antennas to achieve three-dimensional precise beamforming and multi-user beam multiplexing, thereby achieving better coverage and greater capacity.

[0084] See also Figure 6 , Figure 6 A schematic diagram of beam coverage of a Massive MIMO antenna provided in an embodiment of the present application. Figure 6 The left side of is a schematic diagram of the horizontal beam of the Massive MIMO antenna. From the horizontal cross section, the horizontal beam includes 8 beams. The horizontal beam width of the horizontal beam is as follows: Figure 6 As shown, the horizontal beam width is the width of the horizontal beam envelope.

[0085] Figure 6 The middle is a schematic diagram of the vertical beam of the Massive MIMO antenna. From the vertical cross section, the vertical beam includes 4 layers. The vertical beam width of the vertical beam is as follows: Figure 6 As shown, the vertical beam width is the width of the vertical beam envelope. That is to say, the Massive MIMO antenna is divided into 4 layers in the vertical direction, and the horizontal beam corresponding to each layer includes 8 beams, that is, the Massive MIMO antenna has a total of 32 narrow beams, forming different coverage areas in the horizontal and vertical directions.

[0086] Figure 6 The right side is a schematic diagram of an arbitrary beam of a Massive MIMO antenna. For 5G, in addition to adjusting the shape of the horizontal and vertical envelopes as a whole, each narrow beam can also be adjusted independently to form coverage of any shape, such as Figure 6 shown.

[0087] Beam weight (also called antenna weight) refers to the quantitative expression of a specific excitation signal applied to each port of the antenna, in order to obtain specific coverage or achieve the effect of beam deformation. Among them, different beam weights can generate a variety of beam shapes, such as cell-level broadcast beams (SSB beams) and user-level static beams (including SRS beams and CSI-RS beams).

[0088] Among them, the SSB (SS / PBCH blocks) beam is used to stagger the interference between neighboring spaces, and use more beams to achieve spatial coverage to achieve the optimal coverage of the 5G network. The sounding reference signal (SRS) is an uplink pilot signal sent by the terminal device to the network device, which is used to judge the channel quality of each channel in each frequency band. According to the SRS, the network device selects the appropriate channel to dynamically schedule and allocate resources to the terminal device to obtain the best transmission efficiency and quality. The channel state information reference signal (CSI-RS) is a downlink pilot signal sent by the network device to the terminal device, which is used for CSI-RS channel measurement, time-frequency offset tracking, beam management and mobility management. The CSI-RS described in this embodiment refers to the CSI-RS used for mobility management. According to the protocol, the mobility management CSI-RS can measure the beam-level RSRP of the serving cell and its neighboring cells.

[0089] Beam gain (also called antenna gain) refers to the ratio of the power density of the signal generated by the actual antenna and the ideal radiating unit at the same point in space under the condition of equal input power. Among them, beam gain is closely related to the antenna pattern. The narrower the main lobe of the pattern, the smaller the side lobe, and the higher the gain. Antenna gain is used to measure the ability of an antenna to send and receive signals in a specific direction. It is one of the important parameters for selecting base station antennas.

[0090] A measurement report (MR) refers to a measurement report reported by a terminal device, which includes information such as the cell ID of the serving cell, the RSRP of the serving cell, the cell ID of the neighboring cell, the RSRP of the neighboring cell, etc. However, the MR does not include latitude and longitude information.

[0091] MDT is the minimum road test data defined by 3GPP, including the latitude and longitude information reported by the terminal device, the cell ID of the serving cell, the RSRP of the serving cell, the cell ID of the neighboring cell, the RSRP of the neighboring cell, etc. In other words, MDT can be considered as MR with longitude and latitude.

[0092] A site (also called a network device) can be any device with wireless transceiver functions, providing wireless communication services for terminal devices within the coverage area. Sites can include but are not limited to: evolved base stations (NodeB or eNB or e-NodeB, evolutionalNodeB) in long-term evolution (LTE) systems, base stations (gNodeB or gNB) or transceiver points (transmission receiving point / transmission reception point, TRP) in new generation radio access technology (NR), base stations of subsequent evolution of 3GPP, access nodes in WiFi systems, wireless relay nodes, wireless backhaul nodes, devices that assume base station functions in Internet of Vehicles, D2D communication, and machine communication, satellites, etc.

[0093] The terminal device may be a device with wireless transceiver function, or the terminal device may be a chip. The terminal device may be a user equipment (UE), a mobile phone, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a vehicle-mounted terminal device, a wireless terminal in remote medical, a wireless terminal in smart grid, a wearable terminal device, a vehicle network, a sensor in D2D communication, and a machine communication, etc.

[0094] The following will describe it in conjunction with specific embodiments.

[0095] See also Figure 7 , Figure 7 A flowchart of a network configuration method provided in an embodiment of the present application. The network configuration method can be executed by an offline tool deployed offline on a stand-alone computer or cloud, or by an online tool deployed online to a network management system OMC or an online tool platform connected to OMC. The network configuration method is applied in a scenario where there is no MDT data or the MDT data is insufficient, and includes the following steps:

[0096] S701, the network management device aggregates the multiple pieces of measurement report MR data according to the cell information of each MR in the multiple pieces of measurement report MR data to obtain N groups of MR data;

[0097] S702, the network management device obtains an average reference signal received power RSRP of each cell of each group of MRs in N groups of MRs;

[0098] S703, for each group of N groups of MRs, the network management device creates a three-dimensional grid of the group of MRs according to the average RSRP of each cell in the group of MRs and the vertical beam range and the horizontal beam range corresponding to the main beam identifier of each cell;

[0099] S704, for each three-dimensional grid of the MR group, the network management device calculates the path loss between the main beam of each cell in the MR group and the three-dimensional grid to obtain a path loss matrix of the three-dimensional grid;

[0100] S705: The network management device determines the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids.

[0101] In the embodiment of the present application, it is assumed that the measurement report reported by the terminal device does not include longitude and latitude information. That is, the network management device receives the MR reported by the terminal device, but does not include MDT or the MDT is insufficient. In the above scenario, the network management device can aggregate the MR reported by the terminal device to obtain N groups of MR data. Specifically, the network management device can first perform data preprocessing on the MR reported by the terminal device, and the data preprocessing includes MR main beam identification and similar feature MR data aggregation.

[0102] The following is a detailed description of the process of the network management device performing MR main beam identification.

[0103] In addition to receiving the MR reported by the terminal device, the network management device can also obtain the call history record (CHR) of the terminal device. Among them, CHR can record each call of the terminal device in a feature extraction manner. CHR includes the service cell identity (S_Cell_ID), service cell uplink throughput (ULThroughput), service cell downlink throughput (DLThroughput), service main beam identity (S_MainBeam_ID), and can also include access-related information, handover-related information, etc. of the terminal device, which is not limited in this embodiment.

[0104] Optionally, the network management device may also receive an engineering parameter / configuration file and an antenna file. The engineering parameter / configuration file includes information such as radio frequency parameters of each cell, and the antenna file includes a broadcast beam, a horizontal directional pattern of a service beam, a vertical directional pattern of a service beam, beam gain and attenuation information, etc., which are not limited in this embodiment.

[0105] Since MR and CHR are two different types of data reported by the terminal device, MR and CHR can be associated for the convenience of subsequent processing. For example, the network management device can associate MR and CHR according to "call time + Cell_ID + call_ID". Among them, since the number of call_IDs is limited and will be repeated after a period of time, in this embodiment, call_IDs are distinguished by limiting the call time.

[0106] For ease of description, the MR and CHR after association processing in this embodiment are called MR data, which includes one or more MRs. Among them, one MR represents a measurement report reported by a terminal device within a period of time, and the cell information of this MR includes the cell identifiers of one or more cells, the main beam identifiers of one or more cells, and the RSRP of one or more cells. In other words, the cell information of each MR includes the cell identifiers of one or more cells, the main beam identifiers of one or more cells, and the RSRP of one or more cells.

[0107] The serving cell refers to the cell that provides a channel for the terminal device when the terminal device communicates. The neighboring cell refers to the cell adjacent to the serving cell. Figure 2 If cell 2 is the service cell of the terminal device, then cell 3 is the neighboring cell of the terminal device.

[0108] The main beam of the serving cell is the beam with the strongest signal among the multiple beams transmitted by the Massive MIMO antenna detected by the terminal device. In other words, the main beam identifier of the serving cell indicates the beam identifier of the beam with the strongest signal detected by the terminal device.

[0109] For example, after the terminal device accesses the service cell, it can detect multiple beams emitted by the Massive MIMO antenna at the current location. Assume that the Massive MIMO antenna is 64TRx, 64TRx has 64 beams, horizontal 8*vertical 4*polarization 2, such as Figure 8 As shown. It should be noted that the 64 beams (including dual polarization) of the Massive MIMO antenna correspond to 32 physical beam positions, of which the two beams of positive 45-degree polarization and negative 45-degree polarization can be considered as one physical beam. The 32 physical beams have their corresponding beam identifiers. Assuming that the beam identifiers of the 32 physical beams start from 0 to 31, according to the vertical layering, the beam identifiers of the bottom first layer are 0 to 7 from south to north, the beam identifiers of the second layer are 8 to 15 from south to north, the beam identifiers of the third layer are 16 to 23 from south to north, and the beam identifiers of the fourth layer are 24 to 31 from south to north. The beam identifier of the beam with the strongest signal detected by the terminal device is 11, as shown in Figure 8 shown.

[0110] In one implementation, the cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell. That is to say, the relevant information of the neighboring cell is introduced in the embodiment of the present application, so that when the network management device adjusts the network configuration parameters of a cell, it also fully considers the influence of the neighboring cell on it. Specifically, the cell information of each MR includes the cell identity of the serving cell, the RSRP (S_RSRP) of the serving cell, the cell identity (neighbor cell identity, N_Cell_ID) of the neighboring cell, the RSRP (N_RSRP) of the neighboring cell, etc.

[0111] Due to the limitation of the measurement capability of the terminal device, the terminal device cannot obtain the main beam identification of the neighboring cell. To facilitate the subsequent MR main beam identification, this embodiment adds a neighbor main beam identification (N_MainBeam_ID) field in the MR data to record the main beam identification of the neighboring cell.

[0112] MR data can be stored in the network management device in the form of a table or in other forms, which is not limited in this embodiment. Please refer to Table 1, which is an MR data information table provided in the embodiment of the present application. The information table includes fields such as S_Cell_ID, S_RSRP, S_MainBeam_ID, N_Cell_ID, N_RSRP, N_MainBeam_ID, ULThroughput, and DLThroughput. The physical meaning of each field and the source of the field are shown in Table 1.

[0113] Table 1: A MR data information table

[0114]

[0115] It should be noted that the value of the N_MainBeam_ID field can be set to -1 before MR main beam identification. When the MR data is stored after association, it is arranged in the order of service cell and neighboring cell. Among them, different service cells are stored in order of S_RSRP; similarly, neighboring cells are stored in order of N_RSRP.

[0116] Please refer to Table 2, which is a MR data storage table provided in an embodiment of the present application. The storage table includes one or more MRs. The cell information of each MR includes the cell identifier of one or more cells, the main beam identifier of one or more cells, the RSRP of one or more cells, the ULThroughput of one or more cells, and the DLThroughput of one or more cells.

[0117] Table 2: A MR data storage table

[0118]

[0119]

[0120] Among them, the MR with a MainBeam_ID value of -1 in Table 2 refers to a neighboring cell, and the values ​​of ULThroughput and DLThroughput in this row are both 0, that is, the throughput information of the neighboring cell cannot be directly measured by the terminal device.

[0121] In one implementation, in order to facilitate subsequent aggregation of similar feature MR data, the network management device may predict the neighboring area main beam in the MR data, including the following steps:

[0122] s11, for each MR in the MR data, determine the main beam prediction model of the serving cell of the MR according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MR;

[0123] s12, determine the main beam identifier of the neighboring cell of the MR according to the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell and the RSRP of the neighboring cell.

[0124] For example, for all cells in Table 2, obtain the cell information of each cell when it is used as a serving cell. Taking cell i as an example, the network management device can obtain the Cell_ID, RSRP and MainBeam_ID of all cells i including cell i and whose MainBeam_ID value is not -1 from Table 2.

[0125] After traversing all MRs in Table 2, the Cell_ID, RSRP and its corresponding MainBeam_ID of each cell as a serving cell are used as training data, and the training data can be stored in the form of a table. Among them, Cell_ID and RSRP are used as feature vectors, recorded as X_Train, and MainBeam_ID is used as a label, recorded as Y_Train. The training data of the main beam prediction model of the cell is shown in Table 3.

[0126] Table 3: Training data table of a main beam prediction model for a cell

[0127]

[0128] Among them, the serving cell in MR 1 is cell 1, so MainBeam_ID is the MainBeam_ID of cell 1. According to Table 2, the value of MainBeam_ID of cell 1 is 31. It should be noted that MR 1 does not include cell n, so the RSRP value of cell n in MR 1 is 0. The definition of the data in the remaining rows in Table 3 is similar to the definition of MR 1, and will not be repeated here.

[0129] The network management device can use the data in Table 3 as training data and use a machine learning algorithm to train the main beam prediction model. Taking cell i as an example, the main beam prediction model of cell i is recorded as CellBeamModel_cell i. Among them, the training process of the cell main beam prediction model can be simply understood as: for the function y=f(x), x and y are known, and f is obtained by summarizing and induction. That is to say, function y is Y_Train in Table 3, and x is X_Train in Table 3. According to the multiple X_Train and Y_Train stored in Table 3, the main beam prediction model of each cell can be trained. For example, according to the X_Train and Y_Train corresponding to cell i, the main beam prediction model of cell i can be trained.

[0130] Similarly, for all cells in Table 2, the cell information of each cell when it is a neighboring cell is obtained. Taking cell i as an example, the network management device can obtain the Cell_ID and RSRP of all cells i including cell i and the value of MainBeam_ID of cell i is -1 from Table 2. After traversing all MRs in Table 2, the Cell_ID and RSRP of each cell when it is a neighboring cell are used as prediction input values, recorded as X_Pre, and the prediction input values ​​can also be stored in the form of a table, as shown in Table 4.

[0131] Table 4: A prediction input table for neighboring main beam prediction

[0132]

[0133] For cell i, according to X_Pre of cell i and the main beam prediction model of cell i, Y_Pre of cell i can be obtained, that is, the main beam identifier of cell i is predicted. The MR data of all cells with MainBeam_ID value of -1 in Table 2 are traversed, so that all cells in each MR data are marked with the main beam identifier.

[0134] Please refer to Table 5, which is a main beam marked MR data storage table provided in an embodiment of the present application. Compared with Table 2, the value of MainBeam_ID of each cell in Table 5 is greater than -1, that is, the main beam identifier of each cell can indicate one of the beams generated by the Massive MIMO antenna.

[0135] Table 5: MR data storage table after main beam marking

[0136]

[0137] Optionally, since the amount of MR data after the main beam marking is large, it may occupy a large amount of computing resources and reduce the operating efficiency of the OMC. The network management device can aggregate the MR data after the main beam marking according to certain rules. In other words, the network management device can aggregate the MR data with similar characteristics after the main beam marking.

[0138] The following is a detailed description of the process of aggregating similar feature MR data by the network management device.

[0139] The network management device can combine the data features, first perform wireless space propagation similarity analysis on the MR data marked with the main beam, and then aggregate the MR data with wireless space propagation similarity to obtain N groups of MR data.

[0140] Among them, the similarity of wireless space propagation means that wireless signals will have different propagation paths such as refraction, reflection, and diffraction when propagating in space. The same cell transmits a signal, propagates through the wireless space, and reaches the terminal device at a similar distance. Its wireless space propagation is similar. For example, terminal device 1 and terminal device 2 at a similar distance measure the same main beam identifier of the surrounding cells, and the RSRP difference is small. Then it can be said that the wireless space propagation of terminal device 1 and terminal device 2 is similar.

[0141] In one implementation, the network management device may aggregate MR data having wireless space propagation similarity according to each MR in Table 5 and the RSRP of each cell in each MR to obtain N groups of MR data, which may specifically include the following steps:

[0142] MR data with the same cell identifier, the same main beam identifier and a level difference satisfying a preset level difference condition are merged to determine a group of converged MRs; wherein the level difference is the difference in RSRP between two cells with the same cell identifier in the MR data.

[0143] In this embodiment, multiple MRs with the same cell identifier, the same main beam identifier, and a level difference that meets a preset level difference condition (for example, an RSRP difference of less than 3dB) are regarded as MRs with wireless space propagation similarity.

[0144] For example, the network management device may first perform data preprocessing on the MR data after the main beam is marked, wherein Cell_ID, RSRP and MainBeam_ID are used as feature vectors, and the MR data after the main beam is marked is preprocessed to obtain a similar feature MR data aggregation input table, as shown in Table 6.

[0145] Table 6: An input table for similar feature MR data aggregation

[0146]

[0147] The network management device can aggregate the data in Table 6 according to certain clustering rules (such as clustering algorithms) based on the data in Table 6. For example, the network management device aggregates MR data with the same Cell_ID, the same MainBeam_ID and RSRP difference less than 3dB to obtain a group of MRs.

[0148] For example, in Table 6, the MainBeam_ID of cell1 in MR 1 is 31, and the RSRP is 80, and the MainBeam_ID of cell1 in MR 2 is 31, and the RSRP is 78. In Table 6, the MainBeam_ID of cell2 in MR 1 is 29, and the RSRP is 70, and the MainBeam_ID of cell2 in MR 2 is 29, and the RSRP is 70. It can be seen that the cell identifiers of the two MRs are the same, the main beam identifiers of the cells are the same, the difference between the RSRP of cell 1 in MR 1 and the RSRP of cell 1 in MR 2 is less than 3dB, and the RSRP value of cell2 in MR 1 is the same as the RSRP value of cell 1 in MR 2. In other words, MR 1 and MR 2 can be combined into a group of MRs.

[0149] Optionally, when the network management device aggregates the MR data with similar characteristics, the following situations may exist: the cell identifiers in the two MRs are the same, the main beam identifiers of the cells are the same, and the level difference of the cells also meets the preset level difference condition; however, one of the MRs also includes other cell information. For example, for MR 1 and MR 3 in Table 6, MR 1 and MR 3 both include the cell information of cell 1 and the cell information of cell 2. However, MR 3 also includes the cell information of cell 3.

[0150] In order to analyze whether the above MRs can be aggregated into a group of MRs, the network management device can process the MR data with similar characteristics. For example, for each MR in Table 6, the difference between the maximum value of RSRP in each MR and the RSRP of each cell is calculated, and the difference is used as a new feature vector, and Table 6 is expanded as shown in Table 7.

[0151] Table 7: Input table after aggregating and expanding feature vectors of similar feature MR data

[0152]

[0153]

[0154] For example, for MR 1 and MR 3 in Table 7, MR 3 also includes the cell information of cell 3. However, the difference in RSRP of cell 3 in MR 3 is large. That is, compared with the serving cell cell 1, the RSRP of the neighboring cell 3 is smaller, so the distance between cell 3 and cell 1 may be far, that is, cell 3 in the neighboring cell may be invalid and cell 3 can be ignored. In other words, MR 1 and MR 3 can be aggregated into a group of MRs, which have similarity in wireless spatial propagation.

[0155] It should be noted that the data in Table 6 and Table 7 are only a part of the aggregated MR data with similar characteristics. The aggregated MR data also includes the throughput information of the cell, etc., which is not limited in this embodiment.

[0156] Optionally, the network configuration device may determine how many groups of MRs the MR data is aggregated into according to the number of cells, the distribution of users in the cells, the number of users, and the overlapping coverage between cells.

[0157] For example, suppose there are three cells, cell1, cell2, and cell3, where there are no users in cell2 and cell3, and there are two users, UE1 and UE2, in cell1. UE1 is stationary, and its main beam is beam 31; UE2 is a mobile user, and its main beams are beams 8 and 9. The two users reported four MRs respectively, and the processed MR information is shown in Table 8.

[0158] Table 8: Similar feature MR data input table for UE 1 and UE 2

[0159]

[0160] The network management device can aggregate the 4 MR data reported by UE 1 and UE 2, and can be divided into 3 groups through the aggregation operation, wherein the 4 MR data of UE1 are 1 group of MR, and the 4 MR data of UE2 are 2 groups of MR. It should be noted that the above example is only an example, and the number of groups of MRs aggregated by the MR data is obtained by analyzing the specific network conditions, and the basis for the analysis includes the number of cells, the distribution of users in the cells, the number of users, the average RSRP of each cell and other parameters, which are not limited in this embodiment.

[0161] The network management device processes the data of each group of MRs after aggregation, including averaging the RSRP of each group and / or summing the throughput of each group. For example, for the nth group of MRs, the RSRP of the same cell in the group of MRs is averaged to obtain the average RSRP of the same cell in the group of MRs. The uplink throughput of the same cell in the group of MRs is summed to obtain the sum of the uplink throughput of the same cell in the group of MRs. The downlink throughput of the same cell in the group of MRs is summed to obtain the sum of the downlink throughput of the same cell in the group of MRs.

[0162] Optionally, the network management device may also record the number of times each cell in each group of MRs appears. For example, for the nth group of MRs, record the number of times each cell in the group of MRs appears as a serving cell and the number of times each cell in the group of MRs appears as a neighboring cell.

[0163] Please refer to Table 9, which is a format table of MR data after aggregation provided in an embodiment of the present application. Taking the nth group of MR as an example, Table 9 records the cell identifiers of one or more cells in the nth group of MR data, the main beam identifiers of one or more cells, the average RSRP of one or more cells, and other data.

[0164] Table 9: A format of MR data after aggregation

[0165]

[0166] The three-dimensional grid can be regarded as a group of MRs in the converged MR data. That is, the three-dimensional grid n corresponds to the nth group of MRs in the converged MR data.

[0167] Optionally, the stereo grid can also be regarded as a three-dimensional spatial position in a three-dimensional coordinate system. The three dimensions in the three-dimensional coordinate system are different from the conventional three-dimensional coordinate system (such as a three-dimensional coordinate system composed of longitude, latitude and altitude). The three dimensions in the three-dimensional coordinate system are the horizontal beam range corresponding to the main beam identifier of the cell, the vertical beam range and the path loss (also called path loss) from the main beam of the cell to the stereo grid.

[0168] See also Figure 9a , Figure 9a A schematic diagram of a three-dimensional grid provided in an embodiment of the present application. Figure 9a Cell 1 in the example includes 32 narrow beams, where the path loss from beam 1 of cell 1 to stereo grid n is as follows: Figure 9a It should be noted that Figure 9a The multiple stereo grids in represent the three-dimensional space positions. The reference coordinate system is as follows: Figure 9a As shown, that is to say, Figure 9a The three-dimensional space of the illustrated volumetric grid is determined by the antenna planes of the cells and the distances from the cells to the volumetric grid determined by RSRP.

[0169] The network management device can generate a path loss matrix based on multiple three-dimensional grids, engineering parameters / configurations, antenna files, etc. That is, for each three-dimensional grid of a group of MRs, the path loss between the main beam of each cell in the group of MRs and the three-dimensional grid can be calculated to obtain the path loss matrix of the three-dimensional grid, including the following steps:

[0170] s21, according to the main beam identifier of any cell i in the group of MRs, obtain the beam gain corresponding to the main beam identifier of the cell i; the beam gain of the cell i is determined according to the horizontal beam range, the vertical beam range, the antenna gain, the signal attenuation value corresponding to the horizontal beam range, and the signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i;

[0171] s22, calculating the path loss from the main beam of the cell i to the three-dimensional grid of the group of MRs according to the transmit power of the cell i, the beam gain of the cell i and the average RSRP of the cell i.

[0172] Among them, taking the stereo grid n as an example, since the stereo grid n may include multiple cells, when calculating the path loss of the stereo grid n, it is necessary to calculate the path loss from each cell in the stereo grid n to the stereo grid n. The following is a detailed description using celli in the stereo grid n as an example. It should be noted that each cell in all stereo grids can refer to the following steps for calculation to obtain the path loss from each cell in each stereo grid to the stereo grid.

[0173] First, the network management device can obtain the radio frequency parameters of the celli from the engineering parameters / configuration, wherein the radio frequency parameters may include but are not limited to: horizontal beam width, physical azimuth, digital azimuth, vertical beam width, physical downtilt or digital downtilt.

[0174] The horizontal beam width represents the horizontal envelope width of the horizontal plane covered by the beam weight control, for example, Figure 6The horizontal beam width is shown in Figure 1. The vertical beam width indicates the vertical envelope width of the horizontal plane covered by the beam weight control, for example, Figure 6 The vertical beam width shown. The physical azimuth indicates the angle between the facing direction of the physical antenna panel and due north, and its value range is 0 degrees to 359 degrees. The digital azimuth indicates the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north, and its value range is 0 degrees to 359 degrees. The physical downtilt indicates the angle between the plane perpendicular to the physical antenna panel and the horizontal plane, and its value range is -90 degrees to 90 degrees. The digital downtilt indicates the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane, and its value range is -90 degrees to 90 degrees.

[0175] Then, the network management device obtains the horizontal beam range, vertical beam range, antenna gain, signal attenuation value corresponding to the horizontal beam range and signal attenuation value corresponding to the vertical beam range from the antenna file according to the MainBeam_ID of celli.

[0176] For example, the horizontal beam range corresponding to the MainBeam_ID of cell i is [0 degrees, 19 degrees], and the vertical beam range is [3 degrees, 9 degrees]. The antenna gain is 50 dB. Based on the horizontal beam range and the vertical beam range, the network management device can determine the signal attenuation value corresponding to each degree of the horizontal beam range and the signal attenuation value corresponding to each degree of the vertical beam range. According to the calculation formula of the beam gain, the beam gain of the MainBeam_ID of cell i can be calculated. Among them, the calculation formula of the beam gain is as follows: beam gain of the MainBeam_ID of cell i = antenna gain + average value of signal attenuation value. The average value of signal attenuation includes the average value of the signal attenuation value corresponding to the horizontal beam and the average value of the signal attenuation value corresponding to the vertical beam.

[0177] Finally, the network management device can use the classical propagation model formula to calculate the path loss from the main beam of cell i to the stereo grid n. The calculation formula of the path loss is as follows: Path loss from the main beam of cell i to the stereo grid n = Transmit power of cell i + Beam gain of MainBeam_ID of cell i - Average RSRP of cell i. The transmit power of cell i can also be obtained from the antenna file, and the average RSRP of cell i can be obtained from the converged MR data shown in Table 9.

[0178] See also Figure 9b , Figure 9b A schematic diagram of a path loss matrix provided in an embodiment of the present application. Figure 9bThe grid n includes three cells, namely cell 1, cell 2 and cell 3. Taking the three-dimensional grid n as an example, the three-dimensional grid n includes multiple cells and main beam identifiers of the multiple cells, and the path loss from different cells and / or different main beams to the three-dimensional grid n is different. For example, for cell 2, the path loss from beam 0 of cell 2 to the three-dimensional grid n is as follows: Figure 9b However, for cell 1, the path loss from beam 1 of cell 1 to grid n is as follows: Figure 9b As shown, the path loss from beam 0 to stereo grid n is different from that of cell 2.

[0179] The path loss matrix can be stored in the network management device in the form of a table. Please refer to Table 10, which is a data format table of a path loss matrix provided in an embodiment of the present application, including a three-dimensional grid identifier, a cell identifier, a main beam identifier of the cell, and a path loss.

[0180] Table 10: Data format of a path loss matrix

[0181] name Physical meaning Gridn 3D grid logo Cell_ID Cell identification, there are multiple cells in a three-dimensional grid MainBeam_ID Main beam identifier of the cell Road loss Path loss value from cell to three-dimensional grid

[0182] Among them, Gridn represents the nth three-dimensional grid, and each three-dimensional grid has a unique three-dimensional grid identifier. There are multiple cells in a three-dimensional grid, and the cell identifier and main beam identifier of each cell, as well as the path loss from the cell to the three-dimensional grid are all recorded in the path loss matrix.

[0183] The following is a detailed description of the network optimization process.

[0184] According to the description in the above embodiment, the network management device can obtain the three-dimensional grid of N groups of MRs and the path loss matrix from the cell to the three-dimensional grid. If the network has coverage problems and / or capacity problems, the network management device can determine the network configuration parameters of the target cell according to the path loss matrix. In other words, the network management device can adjust the network configuration parameters of the cell with coverage problems and / or capacity problems according to the path loss matrix to solve the coverage problems and / or capacity problems in the network.

[0185] The network configuration parameter may be the RF parameter described in the above embodiment, or a combination of RF parameters. For example, the network configuration parameter (denoted as Conf) adjustable by the network management device may be any one of horizontal beam width, physical azimuth, digital azimuth, vertical beam width, physical downtilt or digital downtilt. For another example, the network management device may determine the combination of RF parameters to be adjusted based on information such as the beam range, traffic flow, RSRP, etc. of the cell in the network, such as adjusting the combination of RF parameters related to the horizontal beam.

[0186] Optionally, the network configuration parameter may also be a configuration parameter in other radio resource management (RRM) scenarios. For example, the network configuration parameter may be a cell individual offset (CIO) parameter used for handover.

[0187] In order to measure whether the network has coverage problems and / or capacity problems, this embodiment uses coverage indicators and / or capacity indicators to quantify the goal of network optimization. Coverage indicators include RSRP, signal to interference plus noise ratio (SINR), overlap coverage ratio, etc., denoted as coverage. Capacity indicators include traffic balance, spectrum efficiency, etc., denoted as capacity.

[0188] RSRP refers to the reception level of a cell, which can be measured by the cell and reported to the network management device. The calculation formula of SINR is as follows: It is determined by the sum of the RSRP of the serving cell, the RSRP of the neighboring cells, and the noise power. The calculation formula for the overlap coverage ratio is as follows: If the difference between the RSRP of the serving cell and the RSRP of the neighboring cell is less than a threshold (for example, 3 dB), it is considered that the serving cell has overlapping coverage and is counted in the number of overlapping coverage serving cells.

[0189] The traffic balance refers to the sum of uplink and downlink throughputs between adjacent cells being as close as possible. In other words, the sum of uplink and downlink throughputs of the serving cell is as close as possible to the sum of uplink and downlink throughputs of the adjacent cells. Spectral efficiency refers to the traffic volume per resource block (RB) per unit time.

[0190] In one implementation, both coverage and capacity may not be optimal at the same time. That is, when the coverage index of the network is adjusted to the optimal state, for example, a larger range can be covered, and the overlapping coverage area is less; however, the capacity index of the network may not be optimal, for example, the spectrum efficiency of some areas is low. In order to optimize the overall performance of the network, the embodiment of the present application proposes a multi-objective, multi-parameter joint optimization. That is, based on the above-mentioned coverage index, capacity index and network configuration parameters, the embodiment of the present application models the target (fitness) of network optimization as the following formula:

[0191] fitness=Func((k 1 *coverage,k 2 *capacity),Conf)

[0192] Among them, fitness represents the joint optimization goal of capacity and coverage, Conf represents the adjustable network configuration parameters, and k 1 represents the coverage weight, k 2 Represents capacity weight. By setting different coverage weights and capacity weights, you can control the impact of coverage and capacity on the joint optimization objective.

[0193] For example, in the current network scenario, the cell covers a hotspot area, and the users in the hotspot area are mostly concentrated in high places (for example, in a 5-story building, users are mostly concentrated on the 4th and 5th floors). In this scenario, the capacity weight can be given priority, that is, k 2 The weight value is greater than k 1 And when adjusting the network configuration parameters, the adjustment of the vertical beam is given priority, that is, the network management device can adjust the parameter combination of the vertical beam width, physical downtilt angle and digital downtilt angle to optimize the capacity and coverage.

[0194] In one implementation, the network management device determines the network configuration parameters of the target cell according to the path loss matrices of N three-dimensional grids, which may include the following steps:

[0195] s31, for each three-dimensional grid, determining a target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid;

[0196] s32, adjusting the network configuration parameters of the target cell according to the preset coverage index and the preset capacity index of the target cell;

[0197] s33, obtaining an adjusted antenna gain of the target cell according to the adjusted network configuration parameters of the target cell;

[0198] s34, determining the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell;

[0199] s35, if the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, determine the adjusted network configuration parameters of the target cell as the network configuration parameters of the target cell.

[0200] Among them, the above s31 can be divided into several small steps, including:

[0201] s311, according to the fitness formula and based on the measured data, determine the three-dimensional grids with coverage problems and / or capacity problems before the network configuration parameters are adjusted;

[0202] s312, using a clustering algorithm to aggregate the three-dimensional grids with coverage problems and / or capacity problems;

[0203] s313, determining that the cell included in the converged problem three-dimensional grid is the target cell.

[0204] The target cell is a cell whose coverage index does not meet the preset coverage index and / or whose capacity index does not meet the preset capacity index. That is to say, the target cell can be determined based on the coverage index of the cell or the capacity index of the cell. It can be understood that the coverage index of the cell refers to the current coverage of the cell, and the capacity index of the cell refers to the current capacity of the cell.

[0205] The preset coverage index may be determined based on parameters such as RSRP, SINR, and overlap coverage ratio; for example, the preset coverage index of a cell is that the overlap coverage ratio of the cell is less than 10%. The preset capacity index may be determined based on parameters such as traffic balance and spectrum efficiency; for example, the preset capacity index of a cell is that the traffic balance of the cell is 1, that is, the sum of the uplink throughput and downlink throughput of the cell is the same as the sum of the uplink throughput and downlink throughput of the adjacent cell.

[0206] For example, the network management device can determine the target cell based on the measured data. The measured data can be determined according to the converged MR data shown in Table 9. The measured data can be the average RSRP of each cell in the three-dimensional grid. If the average RSRP of the cell is lower than the preset RSRP threshold value (for example, 100dB), it is determined that the cell has a coverage problem. The measured data can also be the sum of the uplink and downlink throughputs of each cell in the three-dimensional grid. If the sum of the uplink and downlink throughputs of the cell is less than the preset throughput threshold value, it is determined that the cell has a capacity problem.

[0207] Optionally, when aggregating three-dimensional grids with coverage problems and / or capacity problems, a clustering algorithm (density-based spatial clustering of applications with noise, DBSCAN) etc. may be used. For example, if there are 50 cells with coverage problems and / or capacity problems, three-dimensional grids with higher wireless spatial propagation similarity may be aggregated according to the clustering algorithm. Assuming that the three-dimensional grids aggregated by the clustering algorithm include a total of 30 cells, the network management device may determine the 30 cells as target cells.

[0208] After determining the target cell, the maximum value of the network optimization target is calculated according to the target fitness formula of the network optimization, that is, the target fitness formula of the network optimization is converted into the following formula:

[0209] max{fitness=Func((k 1 *coverage,k 2 *capacity),Conf)}

[0210] Among them, max means the maximum value of fitness that can be obtained by adjusting Conf.

[0211] In one implementation, the network management device can obtain adjustable network configuration parameters from the antenna file, and obtain the current network configuration parameters through configuration and engineering parameters. The network management device can use an optimization algorithm (for example, an operations optimization algorithm based on gradient descent), with max{fitness} as the optimization goal, the current network configuration parameters as the initial value, and the adjustable network configuration parameters as the variable, and continuously adjust Conf in order to obtain the Conf that maximizes fitness; the above optimization process is as follows Fig.10 Among them, the stopping condition of optimization needs to comprehensively consider the efficiency and convergence of the algorithm, that is, the stopping conditions of optimization include: the overall gain reaches the standard (such as fitness reaches the maximum value), or the gain of multiple consecutive rounds is less than the threshold, or the number of iterations reaches the maximum optimization number threshold.

[0212] The embodiment of the present application provides a network configuration method, which can construct a three-dimensional grid based on the average RSRP of each cell in the MR data and the horizontal beam information and vertical beam information corresponding to the main beam identifier of each cell, thereby achieving the goal of constructing a three-dimensional grid without relying on MDT data. In addition, a three-dimensional path loss matrix can be constructed based on the three-dimensional grid to achieve three-dimensional beam optimization. The method can also determine the network configuration parameters of the target cell based on the three-dimensional path loss matrix. By adjusting the network configuration parameters of the target cell, the coverage index and / or capacity index of the target cell can be optimized, thereby facilitating the optimization of network coverage and / or capacity.

[0213] See also Fig.11 , Fig.11 A flowchart of another network configuration method provided by an embodiment of the present application. The network configuration method can be executed by an offline tool deployed offline on a stand-alone computer or cloud, or by an online tool deployed online to a network management system OMC or an online tool platform connected to OMC. The network configuration method is applied in scenarios where MDT data is sufficient or road testing is required, and includes the following steps:

[0214] S1101, a network management device aggregates multiple pieces of minimized road test (MDT) data according to cell information of each piece of MDT in the multiple pieces of MDT data to obtain N groups of MDT data, each group of MDT data including MDTs with the same vertical beam identifier of the cell;

[0215] S1102, for each group of MDTs in the N groups of MDTs, the network management device creates a three-dimensional grid of the group of MDTs according to the longitude and latitude of each cell in the group of MDTs and the vertical beam identifier of each cell;

[0216] S1103, for each three-dimensional grid of the MDT group, the network management device calculates the path loss between the main beam of each cell in the MDT group and the three-dimensional grid to obtain a path loss matrix of the three-dimensional grid;

[0217] S1104: The network management device determines the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids.

[0218] In the embodiment of the present application, it is assumed that the measurement report reported by the terminal device is a measurement report including latitude and longitude information, that is, the terminal device reports MDT data. In the above scenario, the network management device can perform aggregation processing on the MDT reported by the terminal device to obtain N groups of MDT data. Similar to the aggregation processing of MR data by the network management device, the network management device can first perform data preprocessing on the MDT reported by the terminal device, and the data preprocessing includes MDT main beam identification and MDT geographic grid aggregation.

[0219] The following is a detailed description of the process of the network management device performing MDT main beam identification.

[0220] In addition to receiving the MDT reported by the terminal device, the network management device can also obtain the CHR of the terminal device. For the relevant description of CHR, please refer to Figure 7 The description of CHR in the embodiments will not be repeated here.

[0221] Optionally, the network management device can also obtain the engineering parameter / configuration file, antenna file, and electronic map. For the description of the engineering parameter / configuration file and antenna file, please refer to Figure 7 The description of the engineering parameter / configuration file and the antenna file in the embodiment will not be repeated here. The electronic map includes the location information of the geographic space, and can show the location relationship between the site and the terminal device.

[0222] Since MDT and CHR are two different types of data reported by the terminal device, in order to facilitate subsequent processing, MDT and CHR can be associated. The description of the association between MDT and CHR can be referred to Figure 7 The description of the association process between MDT and CHR in the embodiment will not be repeated here.

[0223] For ease of description, the MDT and CHR after the association processing in this embodiment are called MDT data, which includes one or more MDTs. Among them, one MDT represents a measurement report including longitude and latitude information reported by a terminal device within a period of time, and the cell information of this MDT includes the cell identifiers of one or more cells, the main beam identifiers of one or more cells, the RSRP of one or more cells, and the longitude and latitude of one or more cells. In other words, the cell information of each MDT includes the cell identifiers of one or more cells, the main beam identifiers of one or more cells, the RSRP of one or more cells, and the longitude and latitude of one or more cells.

[0224] In one implementation, the cell information of each MDT includes the cell information of the serving cell and / or the cell information of the neighboring cell. That is to say, the relevant information of the neighboring cell is introduced in the embodiment of the present application, so that when the network management device adjusts the network configuration parameters of a cell, it also fully considers the influence of the neighboring cell on it. Specifically, the cell information of each MR includes the cell identity of the serving cell, the RSRP (S_RSRP) of the serving cell, the cell identity (neighbor cell identity, N_Cell_ID) of the neighboring cell, the RSRP (N_RSRP) of the neighboring cell, etc.

[0225] Due to the limitation of the measurement capability of the terminal device, the terminal device cannot obtain the main beam identification of the neighboring cell. To facilitate the subsequent MDT main beam identification, this embodiment adds a neighbor main beam identification (N_MainBeam_ID) field in the MDT data to record the main beam identification of the neighboring cell.

[0226] Similar to MR data, MDT data can be stored in the network management device in the form of a table, or in other forms, which is not limited in this embodiment. Please refer to Table 11, which is an MR data information table provided in an embodiment of the present application. The information table includes fields such as S_Cell_ID, S_RSRP, S_MainBeam_ID, N_Cell_ID, N_RSRP, N_MainBeam_ID, ULThroughput, and DLThroughput. The physical meaning of each field and the source of the field are shown in Table 11.

[0227] Table 11: MDT data information table

[0228]

[0229] Similar to Figure 7In the embodiment, the network management device predicts the neighboring cell main beam in the MR data. In this embodiment, the network management device can also predict the neighboring cell main beam in the MDT data according to similar steps, so that all cells in each MDT data are marked with the main beam identifier.

[0230] Please refer to Table 12, which is a main beam marked MDT data storage table provided in an embodiment of the present application. The main beam identifier of each cell can indicate one of the beams generated by the Massive MIMO antenna.

[0231] Table 12: MDT data storage table after main beam marking

[0232]

[0233] Since the MDT data after the main beam marking only represents the information of the two-dimensional geographic grid, in order to model the three-dimensional grid, the network management device can perform geographic grid aggregation from the vertical plane layer by layer. The following is a detailed description of the process of the network management device performing geographic grid aggregation, which may include the following steps:

[0234] s41, the network management device determines the grid longitude and grid latitude of the plane grid formed by the group of MDTs according to the longitude and latitude of each cell in the group of MDTs;

[0235] s42, the network management device determines the vertical layer where the plane grid of the group of MDTs is located according to the vertical beam identifier of the group of MDTs, so as to obtain the three-dimensional grid of the group of MDTs.

[0236] For example, the network management device can calculate the vertical beam identifier V_Beam_ID corresponding to each cell based on the MDT data marked by the main beam and the MainBeam_ID corresponding to each cell. The formula for calculating V_Beam_ID in the embodiment of the present application is as follows: V_Beam_ID = int(MainBeam_ID ÷ 8). For example, if the MainBeam_ID of the cell is 31, according to the above formula of V_Beam_ID, the V_Beam_ID of the cell is calculated to be 3.

[0237] After the network management device processes the MDT data, the MDT data is as shown in Table 13.

[0238] Table 13: MDT data storage table after vertical beam marking

[0239]

[0240] After the network management device obtains the MDT data marked by the vertical beam, it can aggregate the data of the same vertical layer according to the V_Beam_ID to obtain the MDT data of each vertical layer. In other words, the MDT data of each vertical layer is a group of MDT. For example, according to the V_Beam_ID of each cell in Table 13, the MDT data with the same V_Beam_ID is aggregated to obtain multiple groups of MDT data.

[0241] The network management device can perform geographic grid processing on the MDT data of each vertical layer to obtain the geographic gridded MDT data. The geographic grid processing refers to determining the area formed by each vertical layer projected onto a two-dimensional plane (such as the ground) based on the latitude and longitude information of each vertical layer; and then dividing the two-dimensional plane location area into geographic grids according to a certain ratio. For example, the area formed by the vertical layer V_Beam0 projected onto the ground determined by the latitude and longitude information of the vertical layer V_Beam0 whose V_Beam_ID is V_Beam0 is as follows: Fig.12 Assume that the geographic grid is divided into 20 meters (m)*20m, the vertical layer of V_Beam0 after geographic gridding is projected onto the ground to form the area as shown below: Fig.12 As shown in . For another example, the vertical layer of V_Beam1 is moved upwards by a certain distance in the vertical direction on the basis of being perpendicular to the ground, compared with the vertical layer of V_Beam0, as shown in Fig.12 As shown. That is to say, the area formed by the vertical layer of V_Beam1 projected onto the ground is the same as the area formed by the vertical layer of V_Beam0 projected onto the ground, but the two are located at different heights perpendicular to the ground, that is, the three-dimensional grids of the vertical layers of different V_Beam_IDs are different. It should be noted that the three-dimensional grid here refers to the geographic grid with V_Beam_ID, that is, the three-dimensional grid can be a position in three-dimensional space.

[0242] In one implementation, after the MDT data with the same V_Beam_ID is aggregated, the network management device can also process the data of a group of MDTs with the same V_Beam_ID, including averaging the RSRP of each group and summing the throughput of each group. Figure 7 The description of averaging the RSRP of each group and summing the throughput of each group in the embodiment will not be repeated here.

[0243] Optionally, the network management device may also record the number of times each cell in each MDT group appears. For example, for the nth MDT group, record the number of times each cell in the MDT group appears as a serving cell and the number of times each cell in the MDT group appears as a neighboring cell.

[0244] Please refer to Table 14, which is a table of the format of the MDT data after aggregation provided in an embodiment of the present application. Taking the nth group of MDT as an example, Table 14 records the cell identifiers of one or more cells, the vertical beam identifiers of one or more cells, the average RSRP of one or more cells, the grid longitude, the grid latitude and other data in the nth group of MDT data.

[0245] Table 14: A post-convergence MDT data format

[0246]

[0247] The three-dimensional grid (grid) can be regarded as a group of MRs in the aggregated MDT data. That is, the three-dimensional grid n (Grid n) corresponds to the nth group of MDT in the aggregated MDT data.

[0248] See also Fig.13a , Fig.13a A schematic diagram of another stereo grid provided in an embodiment of the present application. Among them, the path loss from cell 1 to stereo grid n in the V_Beam3 beam, the path loss from cell 2 to stereo grid n in the V_Beam3 beam, and the path loss from cell 3 to stereo grid n in the V_Beam3 beam are as follows: Fig.13a It should be noted that Fig.13a The multiple stereo grids in represent three-dimensional spatial positions respectively. Among them, the two-dimensional geographic plane is determined according to the longitude and latitude. The stereo grid in this embodiment includes a vertical beam identifier, that is, the stereo grid n includes different beam layer data, that is, the stereo grid n is a position in the three-dimensional space.

[0249] The network management device can generate a path loss matrix based on multiple three-dimensional grids, engineering parameters / configurations, antenna files, etc. That is, for each group of MDT three-dimensional grids, the path loss between the main beam of each cell in the group of MDT and the three-dimensional grid can be calculated to obtain the path loss matrix of the three-dimensional grid, including the following steps:

[0250] s51, according to the vertical beam identifier in the group of MDTs, obtaining the vertical beam range corresponding to the vertical beam identifier, the antenna gain, and the signal attenuation value corresponding to the vertical beam range;

[0251] s52, according to the grid longitude and grid latitude of the group of MDTs, obtaining the horizontal beam range, antenna gain and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs;

[0252] s53, calculating the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs according to the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs;

[0253] s54, calculating the path loss from cell i to the three-dimensional grid of the MDT group according to the transmit power of cell i, the antenna gain from cell i to the three-dimensional grid of the MDT group, and the average RSRP of cell i.

[0254] Among them, taking the stereo grid n as an example, since the stereo grid n may include multiple cells, when calculating the path loss of the stereo grid n, it is necessary to calculate the path loss from each cell in the stereo grid n to the stereo grid n. The following is a detailed description taking cell i in the stereo grid n as an example. It should be noted that each cell in all stereo grids can refer to the following steps for calculation to obtain the path loss from each cell in each stereo grid to the stereo grid.

[0255] First, the network management device can obtain the radio frequency parameters of cell i from the engineering parameters / configuration. The radio frequency parameters may include but are not limited to: horizontal beam width, physical azimuth, digital azimuth, vertical beam width, physical downtilt or digital downtilt. For a detailed description of the above radio frequency parameters, please refer to Figure 7 The description in the embodiments will not be repeated here.

[0256] Then, the network management device obtains the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range from the antenna file according to the V_Beam_ID of cell i. For example, the vertical beam range corresponding to the V_Beam_ID of cell i is [3 degrees, 9 degrees]. The antenna gain is 50 dB. Based on the vertical beam range, the network management device can determine the signal attenuation value corresponding to each degree of the vertical beam range.

[0257] The network management device also calculates the horizontal beam range corresponding to the three-dimensional grid n where cell i is located based on the grid longitude, grid latitude, and the engineering parameters of cell i. For example, the horizontal beam range of cell i is [0 degrees, 19 degrees]. Then, based on the horizontal beam range, the signal attenuation value corresponding to each degree of the horizontal beam range is obtained from the antenna file. Based on the above data, the network management device can calculate the antenna gain from cell i to the three-dimensional grid n = the average value of the antenna gain + the signal attenuation value.

[0258] Finally, the network management device can use the classical propagation model formula and combine it with the electronic map to calculate the path loss from cell i to grid n. The calculation formula of the path loss is as follows: Path loss from cell i to grid n = Transmit power of cell i + Antenna gain from cell i to grid n - Average RSRP of cell i. The transmit power of cell i can also be obtained from the antenna file, and the average RSRP of cell i can be obtained from the converged MDT data shown in Table 14.

[0259] See also Fig.13b , Fig.13b A schematic diagram of another path loss matrix provided in an embodiment of the present application. Fig.13b There are three cells in the grid, namely cell 1, cell 2 and cell 3. Taking the three-dimensional grid n as an example, the three-dimensional grid n includes multiple cells and vertical beam identifiers of the multiple cells, and the path loss from different cells to the three-dimensional grid n in different V_Beam_ID beams is different. For example, for cell 2, the path loss from cell 2 to the three-dimensional grid n in the V_Beam0 beam is as follows: Fig.13b As shown, the three-dimensional grid n in the V_Beam0 beam is located at the bottom layer of the multiple layers in the vertical direction, such as Fig.13b shown.

[0260] The path loss matrix can be stored in the network management device in the form of a table. Please refer to Table 15, which is a data format table of another path loss matrix provided in an embodiment of the present application, including a three-dimensional grid identifier, a cell identifier, a vertical beam identifier of the cell, a grid longitude, a grid latitude, and a path loss.

[0261] Table 15: Data format of a path loss matrix

[0262] name Physical meaning Gridn 3D grid logo Cell_ID Cell identification, there are multiple cells in a three-dimensional grid V_Beam_ID Main beam identifier of the cell Longitude Grid longitude Latitude Raster Latitude Road loss Path loss value from cell to vertical beam grid

[0263] Among them, Gridn represents the nth stereo grid, and each stereo grid has a unique stereo grid identifier. There are multiple cells in a stereo grid, and the cell identifier and vertical beam identifier of each cell, grid longitude and grid latitude, and the path loss from the cell to the vertical beam stereo grid are all recorded in the path loss matrix.

[0264] Similar to Figure 7In the process of network optimization in the embodiment, the network management device in this embodiment can also perform network optimization based on the three-dimensional grid of N groups of MRs and the path loss matrix of the three-dimensional grid from the cell to the vertical beam. If the network has coverage problems and / or capacity problems, the network management device can determine the network configuration parameters of the target cell based on the path loss matrix. In other words, the network management device can adjust the network configuration parameters of the cell with coverage problems and / or capacity problems based on the path loss matrix to solve the coverage problems and / or capacity problems in the network. For specific implementation methods, please refer to Figure 7 The description in the embodiments will not be repeated here.

[0265] The embodiment of the present application provides a network configuration method, which can construct a three-dimensional grid based on the latitude and longitude information in the MDT data and the vertical beam identifier determined based on the main beam identifier of the cell, so as to avoid blurring the three-dimensional information by the average processing of the data by the two-dimensional geographic grid, which is conducive to achieving more accurate three-dimensional optimization. In addition, the method can also generate a three-dimensional path loss matrix based on the three-dimensional grid, and the network configuration parameters of the target cell can be determined based on the three-dimensional path loss matrix, which is conducive to optimizing the coverage and / or capacity of the network.

[0266] The following combination Figures 14 to 17 The devices and apparatuses of the embodiments of the present application are described in detail.

[0267] The present application embodiment provides a network management device, such as Fig.14 As shown, the network management device 1400 can be used to implement the network configuration method in the embodiment of the present application. The network management device 1400 may include:

[0268] The aggregation unit 1401 is configured to aggregate the multiple pieces of MR data according to the cell information of each MR in the multiple pieces of measurement report MR data to obtain N groups of MR data, where each group of MR includes MRs with similar wireless space propagation;

[0269] An acquiring unit 1402 is configured to acquire an average reference signal received power RSRP of each cell of each group of MRs in N groups of MRs;

[0270] The creating unit 1403 is used to create a three-dimensional grid of each group of MRs in the N groups of MRs according to the average RSRP of each cell in the group of MRs and the vertical beam range and the horizontal beam range corresponding to the main beam identifier of each cell;

[0271] The calculation unit 1404 is used to calculate the path loss between the main beam of each cell in the group of MRs and the three-dimensional grid for each group of MRs, so as to obtain a path loss matrix of the three-dimensional grid;

[0272] The determination unit 1405 is used to determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet the preset coverage threshold and / or whose capacity index does not meet the preset capacity threshold.

[0273] For specific implementation methods, please refer to Figure 7 The detailed description of S701 to S705 in the embodiment is not repeated here.

[0274] In one implementation, the cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. The determination unit 1405 is specifically used to determine, for each MR, the main beam prediction model of the serving cell of the MR according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MR; and determine the main beam identifier of the neighboring cell of the MR according to the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell.

[0275] For specific implementation methods, please refer to Figure 7 The detailed description of the process of performing MR main beam identification by the network management device in the embodiment will not be repeated here.

[0276] In one implementation, the aggregation unit 1401 is specifically used to aggregate MR data with the same cell identifier, the same main beam identifier, and a level difference that satisfies a preset level difference condition, to determine a group of MRs after aggregation; wherein the level difference is the difference in RSRP between cells with the same cell identifier and the same main beam identifier in the MR data.

[0277] For specific implementation methods, please refer to Figure 7 The detailed description of the process of aggregating similar feature MR data by the network management device in the embodiment will not be repeated here.

[0278] In one implementation, the calculation unit 1404 is specifically configured to:

[0279] According to the main beam identifier of any cell i in the group of MRs, a beam gain corresponding to the main beam identifier of the cell i is obtained; the beam gain of the cell i is determined according to the horizontal beam range, the vertical beam range, the antenna gain, the signal attenuation value corresponding to the horizontal beam range, and the signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i;

[0280] According to the transmit power of cell i, the beam gain of cell i and the average RSRP of cell i, the path loss from the main beam of cell i to the three-dimensional grid of the group of MRs is calculated.

[0281] For specific implementation methods, please refer to Figure 7 The detailed description of the process of calculating the path loss by the network management device in the embodiment will not be repeated here.

[0282] In one implementation, the determining unit 1405 is specifically configured to:

[0283] For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid;

[0284] adjusting the network configuration parameters of the target cell according to the preset coverage index and the preset capacity index of the target cell; obtaining the adjusted antenna gain of the target cell according to the adjusted network configuration parameters of the target cell;

[0285] Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell;

[0286] If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

[0287] For specific implementation methods, please refer to Figure 7 The detailed description of the network optimization process in the embodiment will not be repeated here.

[0288] In one implementation, the network configuration parameter includes one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0289] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0290] In one implementation, Fig.14 The related functions implemented by each unit in can be realized by the processor. Fig.15 , Fig.1515 is a schematic diagram of the structure of a network management device provided in an embodiment of the present application. The network management device may be a device (e.g., a chip) having the function of executing the network configuration described in the embodiment of the present application. The network device 1500 may include a transceiver 1501, at least one processor 1502, and a memory 1503. The transceiver 1501, the processor 1502, and the memory 1503 may be interconnected via one or more communication buses, or may be connected in other ways. In this embodiment, the bus connection method is used as an example, such as Fig.15 shown.

[0291] The transceiver 1501 may be used to send or receive data. For example, the transceiver 1501 may receive MR data reported by a terminal device and a network device. It is understood that the transceiver 1501 is a general term and may include a receiver and a transmitter.

[0292] The processor 1502 may be used to process data. The processor 1502 may include one or more processors, for example, the processor 1502 may be one or more central processing units (CPUs), network processors (NPs), hardware chips, or any combination thereof. When the processor 1502 is a CPU, the CPU may be a single-core CPU or a multi-core CPU.

[0293] Among them, the memory 1503 is used to store program codes, etc. The memory 1503 may include a volatile memory (volatile memory), such as a random access memory (random access memory, RAM). The memory 1503 may also include a non-volatile memory (non-volatile memory), such as a read-only memory (read-only memory, ROM), a flash memory (flash memory), a hard disk drive (hard disk drive, HDD) or a solid-state drive (solid-state drive, SSD). The memory 1503 may also include a combination of the above-mentioned types of memory.

[0294] The processor 1502 may be used to implement the network configuration method in the embodiment of the present application, wherein the specific implementation is as follows:

[0295] Aggregating the multiple MR data according to the cell information of each MR in the multiple measurement report MR data to obtain N groups of MR data, each group of MRs including MRs with similar wireless space propagation;

[0296] Obtain an average reference signal received power RSRP of each cell of each group of MRs in N groups of MRs;

[0297] For each group of N groups of MRs, a three-dimensional grid of the group of MRs is created according to an average RSRP of each cell in the group of MRs and a vertical beam range and a horizontal beam range corresponding to a main beam identifier of each cell;

[0298] For each three-dimensional grid of each group of MRs, the path loss between the main beam of each cell in the group of MRs and the three-dimensional grid is calculated to obtain a path loss matrix of the three-dimensional grid;

[0299] According to the path loss matrices of the N three-dimensional grids, the network configuration parameters of the target cell are determined, wherein the target cell is a cell whose coverage index does not meet a preset coverage threshold and / or whose capacity index does not meet a preset capacity threshold.

[0300] For specific implementation methods, please refer to Figure 7 The detailed description of S701 to S705 in the embodiment is not repeated here.

[0301] In one implementation, the cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. The processor 1502 is also used to determine, for each MR, the main beam prediction model of the serving cell of the MR according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MR; and determine the main beam identifier of the neighboring cell of the MR according to the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell.

[0302] For specific implementation methods, please refer to Figure 7 The detailed description of the process of performing MR main beam identification by the network management device in the embodiment will not be repeated here.

[0303] In one implementation, processor 1502 is also used to aggregate MR data with the same cell identifier, the same main beam identifier, and a level difference that satisfies a preset level difference condition to determine a group of aggregated MRs; wherein the level difference is the difference in RSRP between cells with the same cell identifier and the same main beam identifier in the MR data.

[0304] For specific implementation methods, please refer to Figure 7 The detailed description of the process of aggregating similar feature MR data by the network management device in the embodiment will not be repeated here.

[0305] In one implementation, the processor 1502 is specifically configured to:

[0306] According to the main beam identifier of any cell i in the group of MRs, a beam gain corresponding to the main beam identifier of the cell i is obtained; the beam gain of the cell i is determined according to the horizontal beam range, the vertical beam range, the antenna gain, the signal attenuation value corresponding to the horizontal beam range, and the signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i;

[0307] According to the transmit power of cell i, the beam gain of cell i and the average RSRP of cell i, the path loss from the main beam of cell i to the three-dimensional grid of the group of MRs is calculated.

[0308] For specific implementation methods, please refer to Figure 7 The detailed description of the process of calculating the path loss by the network management device in the embodiment will not be repeated here.

[0309] In one implementation, the processor 1502 is specifically configured to:

[0310] For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid;

[0311] adjusting the network configuration parameters of the target cell according to the preset coverage index and the preset capacity index of the target cell; obtaining the adjusted antenna gain of the target cell according to the adjusted network configuration parameters of the target cell;

[0312] Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell;

[0313] If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

[0314] For specific implementation methods, please refer to Figure 7 The detailed description of the network optimization process in the embodiment will not be repeated here.

[0315] In one implementation, the network configuration parameter includes one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0316] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0317] The present application embodiment provides a network management device, such as Fig.16 As shown, the network management device 1600 can be used to implement the network configuration method in the embodiment of the present application. The network management device 1600 may include:

[0318] The aggregation unit 1601 is used to aggregate the multiple MDT data according to the cell information of each MDT in the multiple minimization of road test MDT data to obtain N groups of MDT data, each group of MDT includes MDTs with the same vertical beam identifier of the cell;

[0319] The creating unit 1602 is configured to create, for each group of MDTs in the N groups of MDTs, a three-dimensional grid of the group of MDTs according to the longitude and latitude of each cell in the group of MDTs and the vertical beam identifier of each cell;

[0320] The calculation unit 1603 is used to calculate the path loss between the main beam of each cell in the group of MDT and the three-dimensional grid for each group of MDT to obtain a path loss matrix of the three-dimensional grid;

[0321] The determination unit 1604 is used to determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet the preset coverage threshold and / or whose capacity index does not meet the preset capacity threshold.

[0322] For specific implementation methods, please refer to Fig.11 The detailed description of S1101 to S1104 in the embodiment will not be repeated here.

[0323] In one implementation, the cell information of each MDT includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. For each MDT, the determining unit 1604 is further configured to:

[0324] Determine a main beam prediction model of the serving cell of the MDT according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MDT;

[0325] Determine the main beam identifier of the neighboring cell of the MDT according to the main beam prediction model of the serving cell of the MDT, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell;

[0326] According to the main beam identifier of each cell in the MDT strip, the vertical beam identifier of each cell in the MDT strip is determined.

[0327] For specific implementation methods, please refer to Fig.11 The detailed description of the process of the network management device performing MDT main beam identification in the embodiment will not be repeated here.

[0328] In one implementation, the creating unit 1602 is specifically configured to:

[0329] Determine, according to the longitude and latitude of each cell in the group of MDTs, a grid longitude and a grid latitude of a plane grid formed by the group of MDTs;

[0330] According to the vertical beam identifier of the group of MDTs, the vertical layer where the plane grid of the group of MDTs is located is determined to obtain the three-dimensional grid of the group of MDTs.

[0331] For specific implementation methods, please refer to Fig.11 The detailed description of the process of geographical grid aggregation performed by the network management device in the embodiment will not be repeated here.

[0332] In one implementation, the calculation unit 1603 is specifically configured to:

[0333] According to the vertical beam identifier in the group of MDTs, a vertical beam range corresponding to the vertical beam identifier, an antenna gain, and a signal attenuation value corresponding to the vertical beam range are obtained;

[0334] According to the grid longitude and grid latitude of the group of MDTs, a horizontal beam range, an antenna gain, and a signal attenuation value corresponding to the horizontal beam range corresponding to a geographic grid determined by the grid longitude and grid latitude in the group of MDTs are obtained;

[0335] Calculate the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs according to the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs;

[0336] The path loss from the cell i to the three-dimensional grid of the MDT group is calculated according to the transmit power of the cell i, the antenna gain from the cell i to the three-dimensional grid of the MDT group, and the average RSRP of the cell i.

[0337] For specific implementation methods, please refer to Fig.11 The detailed description of the process of calculating the path loss matrix of the three-dimensional grid by the network management device in the embodiment will not be repeated here.

[0338] In one implementation, the determining unit 1604 is specifically configured to:

[0339] For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid;

[0340] Adjusting network configuration parameters of the target cell according to a preset coverage indicator and a preset capacity indicator of the target cell;

[0341] According to the adjusted network configuration parameters of the target cell, an adjusted antenna gain of the target cell is obtained;

[0342] Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell;

[0343] If the coverage index of the target cell reaches a preset coverage index, and / or the capacity index of the target cell reaches a preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

[0344] For specific implementation methods, please refer to Figure 7 The detailed description of the network optimization process in the embodiment will not be repeated here.

[0345] In one implementation, the network configuration parameter includes one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0346] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0347] In one implementation, Fig.16 The related functions implemented by each unit in can be realized by the processor. Fig.17 , Fig.171700 is a schematic diagram of the structure of a network management device provided in an embodiment of the present application. The network management device may be a device (e.g., a chip) that has the function of executing the network configuration described in the embodiment of the present application. The network management device 1700 may include a transceiver 1701, at least one processor 1702, and a memory 1703. The transceiver 1701, the processor 1702, and the memory 1703 may be interconnected via one or more communication buses, or may be connected in other ways. In this embodiment, the bus connection method is used as an example, such as Fig.17 shown.

[0348] The transceiver 1701 may be used to send or receive data. For example, the transceiver 1501 may receive MDT data reported by a terminal device and a network device. It is understood that the transceiver 1501 is a general term and may include a receiver and a transmitter.

[0349] The processor 1702 may be used to process data. The processor 1702 may include one or more processors, for example, the processor 1702 may be one or more central processing units (CPUs), network processors (NPs), hardware chips, or any combination thereof. When the processor 1702 is a CPU, the CPU may be a single-core CPU or a multi-core CPU.

[0350] Among them, the memory 1703 is used to store program codes, etc. The memory 1703 may include a volatile memory (volatile memory), such as a random access memory (random access memory, RAM). The memory 1703 may also include a non-volatile memory (non-volatile memory), such as a read-only memory (read-only memory, ROM), a flash memory (flash memory), a hard disk drive (hard disk drive, HDD) or a solid-state drive (solid-state drive, SSD). The memory 1703 may also include a combination of the above-mentioned types of memory.

[0351] The processor 1702 may be used to implement the network configuration method in the embodiment of the present application, wherein the specific implementation is as follows:

[0352] Aggregate multiple pieces of MDT data according to cell information of each piece of MDT in multiple pieces of minimized road test MDT data to obtain N groups of MDT data, each group of MDT including MDTs with the same vertical beam identifier of the cell;

[0353] For each group of MDTs in the N groups of MDTs, a three-dimensional grid of the group of MDTs is created according to the longitude and latitude of each cell in the group of MDTs and the vertical beam identifier of each cell;

[0354] For each three-dimensional grid of the MDT group, the path loss between the main beam of each cell in the MDT group and the three-dimensional grid is calculated to obtain a path loss matrix of the three-dimensional grid;

[0355] According to the path loss matrices of the N three-dimensional grids, the network configuration parameters of the target cell are determined, wherein the target cell is a cell whose coverage index does not meet a preset coverage threshold and / or whose capacity index does not meet a preset capacity threshold.

[0356] For specific implementation methods, please refer to Fig.11 The detailed description of S1101 to S1104 in the embodiment will not be repeated here.

[0357] In one implementation, the cell information of each MDT includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell. For each MDT, the processor 1702 is further configured to:

[0358] Determine a main beam prediction model of the serving cell of the MDT according to the cell identifier of the serving cell, the RSRP of the serving cell, and the main beam identifier of the serving cell in the MDT;

[0359] Determine the main beam identifier of the neighboring cell of the MDT according to the main beam prediction model of the serving cell of the MDT, the cell identifier of the neighboring cell, and the RSRP of the neighboring cell;

[0360] According to the main beam identifier of each cell in the MDT strip, the vertical beam identifier of each cell in the MDT strip is determined.

[0361] For specific implementation methods, please refer to Fig.11 The detailed description of the process of the network management device performing MDT main beam identification in the embodiment will not be repeated here.

[0362] In one implementation, the processor 1702 is specifically configured to:

[0363] Determine, according to the longitude and latitude of each cell in the group of MDTs, a grid longitude and a grid latitude of a plane grid formed by the group of MDTs;

[0364] According to the vertical beam identifier of the group of MDTs, the vertical layer where the plane grid of the group of MDTs is located is determined to obtain the three-dimensional grid of the group of MDTs.

[0365] For specific implementation methods, please refer to Fig.11The detailed description of the process of geographical grid aggregation performed by the network management device in the embodiment will not be repeated here.

[0366] In one implementation, the processor 1702 is specifically configured to:

[0367] According to the vertical beam identifier in the group of MDTs, a vertical beam range corresponding to the vertical beam identifier, an antenna gain, and a signal attenuation value corresponding to the vertical beam range are obtained;

[0368] According to the grid longitude and grid latitude of the group of MDTs, a horizontal beam range, an antenna gain, and a signal attenuation value corresponding to the horizontal beam range corresponding to a geographic grid determined by the grid longitude and grid latitude in the group of MDTs are obtained;

[0369] Calculate the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs according to the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs;

[0370] The path loss from the cell i to the three-dimensional grid of the MDT group is calculated according to the transmit power of the cell i, the antenna gain from the cell i to the three-dimensional grid of the MDT group, and the average RSRP of the cell i.

[0371] For specific implementation methods, please refer to Fig.11 The detailed description of the process of calculating the path loss matrix of the three-dimensional grid by the network management device in the embodiment will not be repeated here.

[0372] In one implementation, the processor 1702 is specifically configured to:

[0373] For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid;

[0374] Adjusting network configuration parameters of the target cell according to a preset coverage indicator and a preset capacity indicator of the target cell;

[0375] According to the adjusted network configuration parameters of the target cell, an adjusted antenna gain of the target cell is obtained;

[0376] Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell and the adjusted network configuration parameters of the target cell;

[0377] If the coverage index of the target cell reaches a preset coverage index, and / or the capacity index of the target cell reaches a preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

[0378] For specific implementation methods, please refer to Figure 7 The detailed description of the network optimization process in the embodiment will not be repeated here.

[0379] In one implementation, the network configuration parameter includes one or more of a horizontal beam width, a physical azimuth, a digital azimuth, a vertical beam width, a physical downtilt, or a digital downtilt;

[0380] Among them, the horizontal beam width represents the horizontal envelope width of the horizontal plane coverage controlled by the beam weight; the vertical beam width represents the vertical envelope width of the horizontal plane coverage controlled by the beam weight; the physical azimuth represents the angle between the facing direction of the physical antenna panel and due north; the digital azimuth represents the angle between the strongest direction of the horizontal beam energy controlled by the beam weight and due north; the physical downtilt represents the angle between the plane perpendicular to the physical antenna panel and the horizontal plane; the digital downtilt represents the angle between the strongest direction of the vertical beam energy controlled by the beam weight and the horizontal plane.

[0381] An embodiment of the present application provides a computer-readable storage medium, which stores a program or instruction. When the program or instruction is executed on a computer, the computer executes the network configuration method in the embodiment of the present application.

[0382] An embodiment of the present application provides a chip or a chip system, which includes at least one processor and an interface, the interface and the at least one processor are interconnected through lines, and the at least one processor is used to run a computer program or instruction to perform the network configuration method in the embodiment of the present application.

[0383] The interface in the chip may be an input / output interface, a pin or a circuit, etc.

[0384] The chip system in the above aspects may be a system on chip (SOC) or a baseband chip, etc., wherein the baseband chip may include a processor, a channel encoder, a digital signal processor, a modem and an interface module, etc.

[0385] In one implementation, the chip or chip system described above in the present application further includes at least one memory, in which instructions are stored. The memory may be a storage unit inside the chip, such as a register, a cache, etc., or a storage unit of the chip (e.g., a read-only memory, a random access memory, etc.).

[0386] An embodiment of the present application provides a communication system, including a network management device, a network device and a terminal device according to an embodiment of the present application.

[0387] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0388] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0389] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A network configuration method, characterized in that: include: Aggregating the multiple pieces of MR data according to the cell information of each MR in the multiple pieces of measurement report MR data to obtain N groups of MR data, each group of MRs includes MRs with similarity in wireless spatial propagation, and the cell information of each MR includes cell identifiers of one or more cells, main beam identifiers of one or more cells, and reference signal received power RSRP of one or more cells; Obtain an average reference signal received power RSRP of each cell of each group of MRs in N groups of MRs; For each group of MRs in the N groups of MRs, a three-dimensional grid of the group of MRs is created according to an average RSRP of each cell in the group of MRs and a vertical beam range and a horizontal beam range corresponding to a main beam identifier of each cell; For each three-dimensional grid of each group of MRs, the path loss between the main beam of each cell in the group of MRs and the three-dimensional grid is calculated to obtain a path loss matrix of the three-dimensional grid; Determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet the preset coverage index and / or whose capacity index does not meet the preset capacity index; The step of calculating the path loss from the main beam of each cell in the group of MRs to the three-dimensional grid for each group of MRs includes: According to the main beam identifier of any cell i in the group of MRs, a beam gain corresponding to the main beam identifier of the cell i is obtained; the beam gain of the cell i is determined according to the horizontal beam range, the vertical beam range, the antenna gain, the signal attenuation value corresponding to the horizontal beam range, and the signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i; Calculate the path loss from the main beam of the cell i to the three-dimensional grid of the group of MRs according to the transmit power of the cell i, the beam gain of the cell i and the average RSRP of the cell i; The determining of the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids includes: For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid; Adjusting network configuration parameters of the target cell according to a preset coverage indicator and a preset capacity indicator of the target cell; According to the adjusted network configuration parameters of the target cell, an adjusted antenna gain of the target cell is obtained; Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell, and the adjusted network configuration parameters of the target cell; If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

2. The method according to claim 1, characterized in that The cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of the one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell; Before aggregating the multiple pieces of MR data according to the cell information of each MR in the multiple pieces of measurement report MR data, the method further includes: For each MR, determine a main beam prediction model of the serving cell of the MR according to the cell identifier of the serving cell in the MR, the RSRP of the serving cell, and the main beam identifier of the serving cell; The main beam identifier of the neighboring cell of the MR is determined according to the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell and the RSRP of the neighboring cell.

3. The method according to claim 1 or 2, characterized in that: The aggregating the multiple pieces of MR data according to the cell information of each MR in the multiple pieces of measurement report MR data to obtain N groups of MR data includes: The MR data with the same cell identifier, the same main beam identifier and the level difference satisfying the preset level difference condition are aggregated and processed to determine a group of aggregated MRs; wherein the level difference is the difference in RSRP between the cells with the same cell identifier and the same main beam identifier in the MR data.

4. A network configuration method, characterized in that: include: Aggregating the multiple pieces of MDT data according to the cell information of each MDT in the multiple pieces of minimized road test MDT data to obtain N groups of MDT data, each group of MDTs includes MDTs with the same vertical beam identifier of the cell, and the cell information of each MDT includes cell identifiers of one or more cells, main beam identifiers of one or more cells, and longitudes and latitudes of one or more cells; the vertical beam identifier of the cell is determined according to the main beam identifier of the cell; For each group of MDTs in the N groups of MDTs, creating a three-dimensional grid of the group of MDTs according to the longitude and latitude of each cell in the group of MDTs and the vertical beam identifier of each cell; For each three-dimensional grid of the MDT group, the path loss between the main beam of each cell in the MDT group and the three-dimensional grid is calculated to obtain a path loss matrix of the three-dimensional grid; Determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet the preset coverage index and / or whose capacity index does not meet the preset capacity index; The step of calculating the path loss from the main beam of each cell in the MDT group to the three-dimensional grid for each group of MDTs includes: According to the vertical beam identifier in the group of MDTs, obtain a vertical beam range corresponding to the vertical beam identifier, an antenna gain, and a signal attenuation value corresponding to the vertical beam range; According to the grid longitude and grid latitude of the group of MDTs, a horizontal beam range, an antenna gain, and a signal attenuation value corresponding to the horizontal beam range corresponding to a geographic grid determined by the grid longitude and grid latitude in the group of MDTs are obtained; Calculate the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs according to the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs; Calculate the path loss from the cell i to the three-dimensional grid of the MDT group according to the transmit power of the cell i, the antenna gain from the cell i to the three-dimensional grid of the MDT group, and the average RSRP of the cell i; The determining of the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids includes: For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid; Adjusting network configuration parameters of the target cell according to a preset coverage indicator and a preset capacity indicator of the target cell; According to the adjusted network configuration parameters of the target cell, an adjusted antenna gain of the target cell is obtained; Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell, and the adjusted network configuration parameters of the target cell; If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

5. The method according to claim 4, characterized in that The cell information of each MDT includes cell information of a serving cell and / or cell information of a neighboring cell, and the RSRP of the one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell; Before aggregating the plurality of pieces of Minimization of Road Test (MDT) data according to the cell information of each piece of MDT in the plurality of pieces of MDT data, the method further includes: For each of the MDTs, determining a main beam prediction model of the serving cell of the MDT according to a cell identifier of the serving cell in the MDT, an RSRP of the serving cell, and a main beam identifier of the serving cell; Determine a main beam identifier of a neighboring cell of the MDT according to a main beam prediction model of a serving cell of the MDT, a cell identifier of the neighboring cell, and an RSRP of the neighboring cell; According to the main beam identifier of each cell in the MDT strip, the vertical beam identifier of each cell in the MDT strip is determined.

6. The method according to claim 5, characterized in that The step of creating a three-dimensional grid of each group of MDTs in the N groups of MDTs according to the longitude, latitude and vertical beam identifier of each cell in the group of MDTs includes: Determine, according to the longitude and latitude of each cell in the group of MDTs, a grid longitude and a grid latitude of a plane grid formed by the group of MDTs; According to the vertical beam identifier of the group of MDTs, the vertical layer where the plane grid of the group of MDTs is located is determined to obtain the three-dimensional grid of the group of MDTs.

7. A network management device, characterized in that: include: a converging unit, configured to perform converging processing on the multiple pieces of MR data according to the cell information of each MR in the multiple pieces of measurement report MR data to obtain N groups of MR data, wherein each group of MRs includes MRs with similarity in wireless spatial propagation, and the cell information of each MR includes cell identifiers of one or more cells, main beam identifiers of one or more cells, and reference signal received power RSRP of one or more cells; An acquiring unit, configured to acquire an average reference signal received power RSRP of each cell of each group of MRs in N groups of MRs; A creating unit, configured to create, for each group of MRs in the N groups of MRs, a three-dimensional grid of the group of MRs according to an average RSRP of each cell in the group of MRs and a vertical beam range and a horizontal beam range corresponding to a main beam identifier of each cell; A calculation unit, configured to calculate, for each three-dimensional grid of each group of MRs, a path loss from a main beam of each cell in the group of MRs to the three-dimensional grid, so as to obtain a path loss matrix of the three-dimensional grid; A determination unit, configured to determine network configuration parameters of a target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet a preset coverage index and / or whose capacity index does not meet a preset capacity index; The calculation unit is used to calculate the path loss between the main beam of each cell in the group of MRs and the three-dimensional grid for each group of MRs, specifically for: According to the main beam identifier of any cell i in the group of MRs, a beam gain corresponding to the main beam identifier of the cell i is obtained; the beam gain of the cell i is determined according to the horizontal beam range, the vertical beam range, the antenna gain, the signal attenuation value corresponding to the horizontal beam range, and the signal attenuation value corresponding to the vertical beam range corresponding to the main beam identifier of the cell i; Calculate the path loss from the main beam of the cell i to the three-dimensional grid of the group of MRs according to the transmit power of the cell i, the beam gain of the cell i and the average RSRP of the cell i; The determining unit is used to determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, specifically for: For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid; Adjusting network configuration parameters of the target cell according to a preset coverage indicator and a preset capacity indicator of the target cell; According to the adjusted network configuration parameters of the target cell, an adjusted antenna gain of the target cell is obtained; Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell, and the adjusted network configuration parameters of the target cell; If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

8. The device according to claim 7, characterized in that The cell information of each MR includes the cell information of the serving cell and / or the cell information of the neighboring cell, and the RSRP of the one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell; the determining unit is further configured to: For each MR, determine a main beam prediction model of the serving cell of the MR according to the cell identifier of the serving cell in the MR, the RSRP of the serving cell, and the main beam identifier of the serving cell; The main beam identifier of the neighboring cell of the MR is determined according to the main beam prediction model of the serving cell of the MR, the cell identifier of the neighboring cell and the RSRP of the neighboring cell.

9. The device according to claim 7 or 8, characterized in that The aggregation unit is used to aggregate the multiple pieces of MR data according to the cell information of each MR in the multiple pieces of measurement report MR data, and is specifically used to: The MR data with the same cell identifier, the same main beam identifier and the level difference satisfying the preset level difference condition are aggregated and processed to determine a group of aggregated MRs; wherein the level difference is the difference in RSRP between the cells with the same cell identifier and the same main beam identifier in the MR data.

10. A network management device, characterized in that: include: a convergence unit, configured to aggregate the multiple pieces of MDT data according to the cell information of each piece of MDT in the multiple pieces of minimized road test MDT data to obtain N groups of MDT data, wherein each group of MDTs includes MDTs with the same vertical beam identifier of the cells, and the cell information of each MDT includes the cell identifiers of one or more cells, the main beam identifiers of one or more cells, and the longitude and latitude of one or more cells; the vertical beam identifier of the cell is determined according to the main beam identifier of the cell; A creating unit, configured to create, for each group of MDTs in the N groups of MDTs, a three-dimensional grid of the group of MDTs according to the longitude and latitude of each cell in the group of MDTs and the vertical beam identifier of each cell; A calculation unit, configured to calculate, for each group of MDT three-dimensional grids, a path loss between a main beam of each cell in the group of MDTs and the three-dimensional grid, so as to obtain a path loss matrix of the three-dimensional grid; A determination unit, configured to determine network configuration parameters of a target cell according to the path loss matrices of the N three-dimensional grids, wherein the target cell is a cell whose coverage index does not meet a preset coverage index and / or whose capacity index does not meet a preset capacity index; The calculation unit is used to calculate the path loss between the main beam of each cell in the group of MDT and the three-dimensional grid for each group of MDT, specifically for: According to the vertical beam identifier in the group of MDTs, obtain a vertical beam range corresponding to the vertical beam identifier, an antenna gain, and a signal attenuation value corresponding to the vertical beam range; According to the grid longitude and grid latitude of the group of MDTs, a horizontal beam range, an antenna gain, and a signal attenuation value corresponding to the horizontal beam range corresponding to a geographic grid determined by the grid longitude and grid latitude in the group of MDTs are obtained; Calculate the antenna gain from any cell i in the group of MDTs to the three-dimensional grid of the group of MDTs according to the vertical beam range, antenna gain, and signal attenuation value corresponding to the vertical beam range corresponding to the vertical beam identifier in the group of MDTs, and the horizontal beam range, antenna gain, and signal attenuation value corresponding to the horizontal beam range corresponding to the geographic grid determined by the grid longitude and grid latitude in the group of MDTs; Calculate the path loss from the cell i to the three-dimensional grid of the MDT group according to the transmit power of the cell i, the antenna gain from the cell i to the three-dimensional grid of the MDT group, and the average RSRP of the cell i; The determining unit is used to determine the network configuration parameters of the target cell according to the path loss matrices of the N three-dimensional grids, specifically for: For each three-dimensional grid, determine the target cell of the three-dimensional grid according to the coverage index and / or capacity index of each cell of the three-dimensional grid; Adjusting network configuration parameters of the target cell according to a preset coverage indicator and a preset capacity indicator of the target cell; According to the adjusted network configuration parameters of the target cell, an adjusted antenna gain of the target cell is obtained; Determine the coverage index and capacity index of the target cell according to the path loss matrix of the three-dimensional grid, the adjusted antenna gain of the target cell, and the adjusted network configuration parameters of the target cell; If the coverage index of the target cell reaches the preset coverage index, and / or the capacity index of the target cell reaches the preset capacity index, the adjusted network configuration parameters of the target cell are determined as the network configuration parameters of the target cell.

11. The device according to claim 10, characterized in that The cell information of each MDT includes cell information of a serving cell and / or cell information of a neighboring cell, and the RSRP of the one or more cells includes the RSRP of the serving cell and / or the RSRP of the neighboring cell; and the determining unit is further configured to: For each of the MDTs, determining a main beam prediction model of the serving cell of the MDT according to a cell identifier of the serving cell in the MDT, an RSRP of the serving cell, and a main beam identifier of the serving cell; Determine a main beam identifier of a neighboring cell of the MDT according to a main beam prediction model of a serving cell of the MDT, a cell identifier of the neighboring cell, and an RSRP of the neighboring cell; According to the main beam identifier of each cell in the MDT strip, the vertical beam identifier of each cell in the MDT strip is determined.

12. The device according to claim 11, characterized in that The creating unit is used to create a three-dimensional grid of each group of MDTs in the N groups of MDTs according to the longitude, latitude and vertical beam identifier of each cell in the group of MDTs, specifically for: Determine, according to the longitude and latitude of each cell in the group of MDTs, a grid longitude and a grid latitude of a plane grid formed by the group of MDTs; According to the vertical beam identifier of the group of MDTs, the vertical layer where the plane grid of the group of MDTs is located is determined to obtain the three-dimensional grid of the group of MDTs.

13. A network management device, characterized in that: include: Memory and processor; The memory is used to store computer instructions; The processor is configured to execute the computer instructions so that the method according to any one of claims 1 to 3 is performed.

14. A network management device, characterized in that: include: Memory and processor; The memory is used to store computer instructions; The processor is configured to execute the computer instructions so that the method according to any one of claims 4 to 6 is performed.

15. A computer-readable storage medium, characterized in that: The method comprises a program or a computer instruction. When the program or the computer instruction is run on a computer, the method according to any one of claims 1 to 6 is executed.

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