WO2021114192A1

WO2021114192A1 - Network parameter adjustment method and network management device

Info

Publication number: WO2021114192A1
Application number: PCT/CN2019/124958
Authority: WO
Inventors: 朱重明; 徐志节; 陈志堂; 揣捷; 沈非一; 吕文龙; 卫星
Original assignee: 华为技术有限公司
Priority date: 2019-12-12
Filing date: 2019-12-12
Publication date: 2021-06-17
Also published as: CN114375589B; CN114375589A

Abstract

The embodiments of the present application disclose a network parameter adjustment method and a network management device, relating to the field of communications. The method optimizes cluster performance by means of adjusting a network parameter for each cell within a cluster. Said method comprises: determining state information for a first cell group, wherein said state information is used for indicating a traffic counter indicator for the first cell group, the first cell group comprising at least two cells, and the performance of the at least two cells mutually influencing each other; determining a target value of a first network parameter for each cell within the first cell group according to the state information for the first cell group and a network parameter recommendation algorithm; the network parameter recommendation algorithm is used to describe a correlation between state information, a network parameter, and a performance indicator for the first cell group, wherein a first performance indicator for the first cell group is best when the value of the first network parameter for every cell is the corresponding target value.

Description

Network parameter adjustment method and network management equipment

Technical field

The embodiments of the present application relate to the field of communications, and in particular, to a network parameter adjustment method and network management equipment.

Background technique

The adjustment of wireless network parameters will have an impact on the performance of the wireless network. In order to improve network performance, wireless network parameters can be adjusted. After adjusting a certain parameter of a cell, the performance of the cell changes, and in addition, it may also affect the performance of the neighboring cells of the cell. The current cell and the affected neighboring cell can be called a cluster, and the parameters that affect the cluster are called cluster parameters.

The prior art can model a single cell, and determine the network parameters of the cell, such as intra-frequency handover parameters, inter-frequency handover parameters, cell system parameters, etc., according to the coverage characteristics of the cell and the optimization target of cell performance. The network side can configure the cell based on these parameters to improve cell performance.

This method can only optimize the performance of a certain cell in the cluster, and may affect the performance of neighboring cells. For example, after the intra-frequency handover parameters of the cell are adjusted, the user rate of the cell increases, but the user rate of the neighboring cell decreases.

Summary of the invention

The embodiments of the present application provide a network parameter adjustment method and network management equipment, which optimize the performance of the cluster by adjusting the network parameters of each cell in the cluster.

In a first aspect, a method for adjusting network parameters is provided. The method includes: a network management device can determine status information of a first cell group; wherein the status information is used to indicate a traffic statistics index of the first cell group. The group includes at least two cells, and the performance of the at least two cells influence each other. The network management device may also recommend optimized network parameters, and configure the cells included in the first cell group according to the optimized network parameters, which can improve the performance of the first cell group. Specifically, the target value of the first network parameter of each cell in the first cell group can be determined according to the status information of the first cell group and the network parameter recommendation algorithm; the network parameter recommendation algorithm is used to describe the status information, network parameters, and Correspondence between the performance indicators of the first cell group. When the value of the first network parameter of each cell is the corresponding target value, the first performance indicator of the first cell group is the best.

In the method provided by the embodiment of the present application, the network management device may use the state information of the first cell group as the input of the network parameter recommendation algorithm to determine the first performance of the first cell group under different values of the first network parameter. index. Finally, the value of the first network parameter that makes the first performance index of the first cell group the best is selected, that is, the target value of the embodiment of the present application. The input of the network parameter recommendation algorithm is the status information of the cell group and the network parameters of each cell in the cell group, and the output is the performance index of the cell group. Keep the state information of the cell group unchanged, the value of the first network parameter is different, and the level of the first performance index of the cell group is different. It can be seen that the embodiment of the present application is different from the prior art, and does not need to be limited to a single cell for performance optimization, and ignores the performance of the entire cell group. The method provided in the embodiments of the present application can optimize the performance of a cell group (for example, a cluster) by adjusting network parameters.

With reference to the first aspect, in a first possible implementation manner of the first aspect, the determining the status information of the first cell group includes: determining the first cell group according to the traffic statistics index of each of the at least two cells Status information of the group.

In the method provided in the embodiments of the present application, the state information of each cell in the cell group can be calculated to obtain the state information of the cell group, and combined with the network parameter recommendation algorithm, it is predicted that the state of the cell group does not change. The performance index of the first cell group when the network parameters take different values.

With reference to the first aspect or the first possible implementation manner of the first aspect, in the second possible implementation manner of the first aspect, the first cell group is determined according to the state information of the first cell group and the network parameter recommendation algorithm The target value of the first network parameter of each cell in the group includes: determining the first target value corresponding to the i-th cell in the first cell group according to the network parameter recommendation algorithm; except for the i-th cell in the first cell group The value of the first network parameter of the remaining cells outside the cell is the default value, and the value of the first network parameter of the i-th cell is the first target value when the first performance index of the first cell group is higher than that of the i-th cell The value of the first network parameter of is the first performance index of the first cell group when the remaining candidate values are the remaining candidate values; i is an integer greater than or equal to 1; the i+1th cell in the first cell group is determined according to the network parameter recommendation algorithm The corresponding second target value; the value of the first network parameter of the first i cell in the first cell group is the corresponding target value, and the first network parameter of the remaining cells in the first cell group except the first i cell The value of is the default value, the value of the first network parameter of the i+1th cell is the second target value and the value of the first network parameter of the first i cell is the corresponding target value. Performance index, the first performance index of the first cell group when the value of the first network parameter of the i+1th cell is higher than the remaining candidate values and the value of the first network parameter of the first i cell is the corresponding target value .

In the method provided in the embodiments of the present application, the target values of the network parameters of the cells in the cell group are determined one by one, and the values of the first network parameters of the cells in the cell group are integrated to obtain the best performance index. Different from the traditional traversal algorithm, it can reduce the computing load of the network management equipment.

With reference to the first aspect or the first or second possible implementation manner of the first aspect, in the third possible implementation manner of the first aspect, the state information of at least one cell group is determined; for at least one cell group The state information, at least one network parameter, and at least one performance index are learned to determine the network parameter recommendation algorithm.

In the method provided in the embodiments of the present application, the network management device can also use a machine learning model to learn historical indicators of multiple cells to obtain a network parameter recommendation algorithm to predict the cell group’s performance based on the status information and network parameters of the cell group. Performance.

With reference to the third possible implementation manner of the first aspect, in the fourth possible implementation manner of the first aspect, determining the state information of at least one cell group includes: for each cell in the at least one cell group The group determines the status information of the cell group according to the traffic statistics index of each cell in the cell group.

In the method provided by the embodiment of the present application, the traffic statistics index of each cell in the cell group can be calculated to obtain the state information of the cell group, and the machine learning model can be input for learning to obtain the network parameter recommendation algorithm.

With reference to the first aspect or any one of the first to fourth possible implementation manners of the first aspect, in the fifth possible implementation manner of the first aspect, the first network parameter is any one of the following parameters : Cell system parameters, intra-frequency cell handover threshold, inter-frequency cell handover threshold or load balancing parameters.

The embodiments of the present application provide specific implementations of network parameters, and the performance of the cell group can be changed by adjusting the values of the foregoing network parameters.

With reference to the first aspect or any one of the first to fifth possible implementation manners of the first aspect, in the sixth possible implementation manner of the first aspect, at least two cells are co-frequency cells, or, At least two cells are inter-frequency cells, or at least two cells belong to the same sector, or at least two cells belong to the same single-frequency networking SFN area.

The embodiment of the present application provides a specific implementation of a cell group, where a cluster may include at least two same-frequency or at least two different-frequency cells, and a cluster may be a sector or an SFN area. The method provided in the embodiment of the present application improves the performance of the cluster by adjusting the network parameters of the cell.

In a second aspect, a network management device is disclosed, including: a parameter processing unit, configured to determine status information of a first cell group; wherein the status information is used to indicate a traffic statistics index of the first cell group, and the first cell group The group includes at least two cells, and the performance of the at least two cells influences each other; a parameter recommendation unit for determining the first network of each cell in the first cell group according to the status information of the first cell group and a network parameter recommendation algorithm The target value of the parameter; the network parameter recommendation algorithm is used to describe the correspondence between the status information, network parameters, and the performance indicators of the first cell group. When the value of the first network parameter of each cell is the corresponding target value, the first The first performance index of a cell group is the best.

With reference to the second aspect, in the first possible implementation manner of the second aspect, the parameter processing unit is specifically configured to determine the state information of the first cell group according to the traffic statistics index of each of the at least two cells.

With reference to the second aspect or the first possible implementation manner of the second aspect, in the second possible implementation manner of the second aspect, the parameter recommendation unit is specifically configured to determine the first cell group in the first cell group according to the network parameter recommendation algorithm The first target value corresponding to the i-th cell; the value of the first network parameter of the remaining cells in the first cell group except the i-th cell is the default value, and the value of the first network parameter of the i-th cell The first target value is the first performance index of the first cell group, and the value of the first network parameter higher than the i-th cell is the first performance index of the first cell group when the remaining candidate values are used; i is greater than or equal to 1 Integer of; Determine the second target value corresponding to the i+1th cell in the first cell group according to the network parameter recommendation algorithm; The value of the first network parameter of the first i cell in the first cell group is the corresponding target Value, the value of the first network parameter of the remaining cells in the first cell group except the first i cell is the default value, the value of the first network parameter of the i+1th cell is the second target value and the value of the first i The value of the first network parameter of the cell is the first performance index of the first cell group when the value of the first cell group is the corresponding target value, and the value of the first network parameter higher than the i+1th cell is the remaining candidate values and the value of the first i The value of the first network parameter is the first performance index of the first cell group when the value is corresponding to the target value.

In combination with the second aspect or the first or second possible implementation manner of the second aspect, in the third possible implementation manner of the second aspect, the parameter recommendation module is also used to determine the status information of at least one cell group ; Learning the state information of at least one cell group, at least one network parameter, and at least one performance index to determine a network parameter recommendation algorithm.

With reference to the second aspect or the first to third possible implementation manners of the second aspect, in the fourth possible implementation manner of the second aspect, the parameter recommendation unit is specifically configured to target each cell group in at least one cell group. For a cell group, the status information of the cell group is determined according to the traffic statistics index of each cell in the cell group.

With reference to the second aspect or the first to fourth possible implementation manners of the second aspect, in the fifth possible implementation manner of the second aspect, the first network parameter is any one of the following parameters: cell system parameters, Same frequency cell handover threshold, different frequency cell handover threshold or load balancing parameter.

With reference to the second aspect or the first to fifth possible implementation manners of the second aspect, in the sixth possible implementation manner of the second aspect, at least two cells are co-frequency cells, or at least two cells are Inter-frequency cells, or, at least two cells belong to the same sector, or, at least two cells belong to the same single-frequency networking SFN area.

In a third aspect, an embodiment of the present application provides a communication network management device, which can implement the foregoing first aspect or the method in any possible implementation manner of the first aspect. The network management device includes corresponding units or components for executing the above-mentioned methods. The units included in the network management device can be implemented in software and/or hardware. The network management device may be a network device, or a chip, a chip system, or a processor that can support the network device to implement the foregoing method.

In a fourth aspect, the present application provides a communication network management device, including: a processor, the processor is coupled with a memory, the memory is used to store a program or instruction, when the program or instruction is executed by the processor , So that the network management device implements the foregoing first aspect or the method described in any one of the possible implementation manners of the first aspect.

In a fifth aspect, the present application provides a storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed, the computer executes the first aspect or any one of the possible implementations of the first aspect The method described.

In a sixth aspect, an embodiment of the present application provides a communication system, including: the network management device, the network device according to the second aspect; or, the network management device, the network device, and the terminal device according to the second aspect.

Description of the drawings

FIG. 1 is a schematic diagram of a communication system provided by an embodiment of this application;

2 is a structural block diagram of a network management device provided by an embodiment of the application;

FIG. 3 is a schematic diagram of a cluster provided by an embodiment of the application;

FIG. 4 is a schematic diagram of intra-frequency handover provided by an embodiment of the application;

FIG. 5 is a schematic diagram of inter-frequency handover provided by an embodiment of the application;

FIG. 6 is a schematic flowchart of a network parameter adjustment method provided by an embodiment of this application;

FIG. 7 is another structural block diagram of a network management device provided by an embodiment of the application;

Fig. 8 is another structural block diagram of a network management device provided by an embodiment of the application.

Detailed ways

Figure 1 shows a schematic diagram of a communication system to which the technical solution provided by this application is applicable. The communication system may include multiple network devices (only network device 100 is shown) and multiple terminal devices (only shown in the figure). The terminal device 201 and the terminal device 202) and the network management device 300 are included. FIG. 1 is only a schematic diagram, and does not constitute a limitation on the applicable scenarios of the technical solutions provided in this application.

Among them, the network device and the terminal device can communicate through a cellular link (Uu link). For example, the network device 100 and the terminal device 201 can communicate with each other, and the terminal device can communicate through a side link (sidelink link). For communication, for example, the terminal device 201 and the terminal device 202 can communicate, and the sidelink link may include D2D communication, V2X communication, and machine type communication (MTC).

The network device 100 may be any device with a wireless transceiving function. Including but not limited to: evolved base station in LTE (NodeB or eNB or e-NodeB, evolutional NodeB), base station in NR (gNodeB or gNB) or transmission receiving point/transmission reception point (TRP), 3GPP Subsequent evolution of base stations, access nodes in the WiFi system, wireless relay nodes, wireless backhaul nodes, etc. The base station can be: a macro base station, a micro base station, a pico base station, a small station, a relay station, or a balloon station, etc. Multiple base stations can support networks of the same technology mentioned above, or networks of different technologies mentioned above. The base station can contain one or more co-site or non-co-site TRPs. The network device may also be a wireless controller, a centralized unit (CU), and/or a distributed unit (DU) in a cloud radio access network (cloud radio access network, CRAN) scenario. The network device can also be a server, a wearable device, or a vehicle-mounted device. The following description takes the network device as a base station as an example. The multiple network devices may be base stations of the same type, or base stations of different types. The base station can communicate with the terminal equipment, and it can also communicate with the terminal equipment through the relay station. The terminal device can communicate with multiple base stations of different technologies. For example, the terminal device can communicate with a base station that supports an LTE network, can also communicate with a base station that supports a 5G network, and can also support communication with a base station of an LTE network and a base station of a 5G network. Double connection.

A terminal device (such as terminal device 201 or terminal device 202) is a device with wireless transceiver function, which can be deployed on land, including indoor or outdoor, handheld, wearable, or vehicle-mounted; it can also be deployed on water (such as ships, etc.) ; Can also be deployed in the air (such as aircraft, balloons and satellites, etc.). The terminal may be a mobile phone (mobile phone), a tablet computer (Pad), a computer with wireless transceiver function, virtual reality (VR) terminal equipment, augmented reality (AR) terminal equipment, industrial control (industrial control) Wireless terminals in control), vehicle-mounted terminal equipment, wireless terminals in unmanned driving (self-driving), wireless terminals in remote medical (remote medical), wireless terminals in smart grid (smart grid), transportation safety (transportation safety) Wireless terminals in ), wireless terminals in smart cities, wireless terminals in smart homes, wearable terminal devices, and so on. The embodiments of this application do not limit the application scenarios. Terminals can sometimes be referred to as terminal equipment, user equipment (UE), access terminal equipment, vehicle-mounted terminal, industrial control terminal, UE unit, UE station, mobile station, mobile station, remote station, remote terminal equipment, mobile Equipment, UE terminal equipment, terminal equipment, wireless communication equipment, UE agent or UE device, etc. The terminal can also be fixed or mobile. The terminal device of the present application may also be a vehicle-mounted module, vehicle-mounted module, vehicle-mounted component, vehicle-mounted chip, or vehicle-mounted unit built into a vehicle as one or more components or units. The vehicle passes through the built-in vehicle-mounted module, vehicle-mounted module, An on-board component, on-board chip, or on-board unit can implement the method of the present application.

The network management device 300 is configured to manage the network device 100, for example, send network parameters to the network device 100, so that the network device 100 configures a cell according to the network parameters sent by the network management device 300.

In the prior art, the network management device 300 can deliver the network parameters that need to be adjusted for the cell to the network device 100 according to the coverage feature of a certain cell and the optimization target of the cell performance. The network device 100 can configure the cell according to these parameters to improve the performance of the cell.

An embodiment of the present application provides a method for adjusting network parameters. A network management device determines state information of a first cell group; wherein the state information is used to indicate a traffic statistics indicator of the first cell group. In addition, the first cell group (for example, the first cell group may be a cluster) includes at least two cells, and the performance of the at least two cells influence each other. The network device may also use the state information of the first cell group as an input of the network parameter recommendation algorithm to determine the first performance index of the first cell group under different values of the first network parameter. Finally, the value of the first network parameter that makes the first performance index of the first cell group the best is selected, that is, the target value described in the embodiment of the present application. Among them, the network parameter recommendation algorithm is used to describe the correspondence between the status information of the cell group, network parameters, and the performance indicators of the cell group. The input of the network parameter recommendation algorithm is the status information of the cell group and each cell group. The network parameters of the cell are output as the performance index of the cell group. Keep the state information of the cell group unchanged, the value of the first network parameter is different, and the level of the first performance index of the cell group is different. It can be seen that the embodiment of the present application is different from the prior art, and does not need to be limited to a single cell for performance optimization, and ignores the performance of the entire cell group. The method provided in the embodiments of the present application can optimize the performance of a cell group (for example, a cluster) by adjusting network parameters.

Fig. 2 shows a schematic diagram of the hardware structure of a network management device provided by an embodiment of the application. The network management device may be the network management device described in the embodiment of the present application. Referring to FIG. 2, the network management device includes a processor 201, a memory 202, and at least one network interface (FIG. 2 is only an example, taking the network interface 203 as an example for illustration). Among them, the processor 201, the memory 202, and the network interface 203 are connected to each other.

The processor 201 can be a general-purpose central processing unit (central processing unit, CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more programs for controlling the execution of the program of this application. integrated circuit.

The network interface 203 is an interface of a network management device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), and so on.

The memory 202 can be a read-only memory (ROM) or other types of static data centers that can store static information and instructions, random access memory (RAM), or other types that can store information and instructions The dynamic data center can also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disk storage, optical disc storage (Including compact discs, laser discs, optical discs, digital universal discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic data centers, or can be used to carry or store desired program codes in the form of instructions or data structures and can be used by a computer Any other media accessed, but not limited to this. The memory can exist independently and is connected to the processor through a communication line. The memory can also be integrated with the processor.

The memory 202 is used to store computer-executed instructions for executing the solution of the present application, and the processor 201 controls the execution. The processor 201 is configured to execute computer-executable instructions stored in the memory 202, so as to implement the intention processing method provided in the following embodiments of the present application.

Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application program codes, which are not specifically limited in the embodiments of the present application.

In a specific implementation, as an embodiment, the processor 201 may include one or more CPUs, such as CPU0 and CPU1 in FIG. 2.

In a specific implementation, as an embodiment, the network management device may include multiple processors, such as the processor 201 and the processor 204 in FIG. 2. Each of these processors can be a single-CPU (single-CPU) processor or a multi-core (multi-CPU) processor. The processor here may refer to one or more devices, circuits, and/or processing cores for processing data (for example, computer program instructions).

In a specific implementation, as an embodiment, the network management device may further include an output device 204 and an input device 205. The output device 204 communicates with the processor 201 and can display information in a variety of ways. For example, the output device 204 may be a liquid crystal display (LCD), a light emitting diode (LED) display device, a cathode ray tube (CRT) display device, or a projector (projector) Wait. The input device 205 communicates with the processor 201, and can receive user input in a variety of ways. For example, the input device 205 may be a mouse, a keyboard, a touch screen device, a sensor device, or the like.

The aforementioned network management device may be a general-purpose device or a special-purpose device. In a specific implementation, the network management device can be a desktop computer, a network network management device, an embedded device, or other devices with a similar structure in FIG. 2. The embodiments of this application do not limit the type of network management equipment.

First, explain the terms involved in the embodiments of this application:

(1) Community group

The cell group includes at least two cells, and the performance of the cells affect each other. It is understandable that if the performance of a certain cell in the cell group changes, the performance of other cells in the cell group will also change. The cell group in the embodiment of the present application may be a cluster, a single frequency network (SFN) area, a sector, and so on. The cells in the cell group can be intra-frequency cells or inter-frequency cells.

Among them, the cluster can be determined by adjusting network parameters. For example, referring to Fig. 3, adjusting the network parameter P of cell A, the performance of cell A changes, while the performance of cell C and cell D are affected, and the performance of cell B and cell E is not affected. For the network parameter P, there are clusters including cell A, cell C, and cell D.

Specifically, the sector can be determined according to the engineering parameters corresponding to the cell. For example, if the latitude and longitude of the sites where different cells are located are the same, and the respective direction angles are also the same, the cells belong to the same sector.

(2) Status information

In this embodiment of the application, the status information is used to indicate traffic statistics indicators. Wherein, the traffic statistics index may be a counter (statistical) index. For example, the status information of a cell is used to indicate the counter index of the cell, for example, the number of users, traffic, coverage, interference, etc. of the cell.

The status information of the cell group is used to indicate the counter index of the cell group, and the counter index of the cell group can be determined according to the counter index of each cell in the cell group. Specifically, a designated algorithm can be used to calculate the counter indicators of each cell to obtain the counter indicators of the cell group. For example, the counter index of each cell in the cell group can be summed to obtain the counter index of the cell group.

For example, the cluster includes cell A, cell C, and cell D. The number of users in cell A is 500, the number of users in cell C is 380, and the number of users in cell D is 420. Then the number of users in the cluster is 500+380+420= 1300. Or, the traffic of cell A is X ₁ , the traffic of cell C is X ₂ , the traffic of cell D is X ₃ , and the traffic of cluster is a*X ₁ +c*X ₂ +d*X ₃ , where a, c , D are the corresponding weight coefficients of A, cell C and cell D.

(3) Network parameters

The network parameters are the configuration parameters of the cell, and adjusting the values of the configuration parameters of the cell can have an impact on the performance of the cell. In the embodiment of the present application, the network parameter may be a configuration parameter of the cell that affects the performance of the cell and other cells in the cell group. It is understandable that after adjusting the value of a certain network parameter of the cell, the performance of the cell has changed, and the performance of other cells in the cell group has also changed. It can be considered that the performance of the cell group has changed. . In the embodiments of the present application, the network parameter influence may be referred to as cell coordination type parameters, group-level network parameters, etc. The embodiments of the present application do not limit the names of the network parameters.

For example, the network parameters may be cell system parameters, intra-frequency cell handover thresholds, inter-frequency cell handover thresholds, or load balancing parameters.

Specifically, the cell system parameters are parameters used to control cell system performance and KPIs, which may be cell scheduling parameters, power control parameters, trigger threshold parameters, and the like.

The same-frequency cell handover threshold is used to control the handover of terminal equipment between cells of the same frequency. For example, referring to Fig. 4, the terminal equipment resides in cell A. When the signal reception quality measured by the terminal equipment meets the intra-frequency cell handover threshold, the terminal equipment switches to the intra-frequency cell B of cell A. Among them, same-frequency cells refer to cells with the same center frequency.

It should be noted that the handover of terminal equipment between cells of the same frequency can affect the performance of cells of the same frequency. Therefore, adjusting the switching threshold of the same frequency cells can affect the performance of cells of the same frequency. In a possible implementation, the cell group includes same-frequency cells, and after adjusting the same-frequency handover threshold, the performance of the cell group may change. In the embodiment of the present application, the intra-frequency cell handover threshold is considered to be a network parameter that affects the performance of the cell group.

Optionally, the same-frequency cell handover threshold may be the trigger threshold of the A1 event. When the trigger threshold of the A1 event is met, the A1 event is triggered, and the terminal equipment camped in the cell switches to other cells with the same frequency as the cell.

The inter-frequency cell handover threshold is used to control the handover of terminal equipment between inter-frequency cells. For example, referring to FIG. 5, the terminal device resides in cell A. When the signal reception quality measured by the terminal device meets the inter-frequency cell switching threshold, the terminal device switches to the inter-frequency cell C of cell A. Among them, inter-frequency cells refer to cells with different central frequency points.

It should be noted that the handover of the terminal equipment between inter-frequency cells can affect the performance of the inter-frequency cell. Therefore, adjusting the inter-frequency cell switching threshold can affect the performance of the inter-frequency cell. In a possible implementation, the cell group includes inter-frequency cells. After the inter-frequency handover threshold is adjusted, the performance of the cell group may change. In the embodiments of the present application, the inter-frequency cell handover threshold is considered to be a network parameter that affects the performance of the cell group.

Optionally, the inter-frequency cell handover threshold may be the trigger threshold of the A3 event. When the trigger threshold of the A3 event is met, the A3 event is triggered, and the terminal equipment camped in the cell is switched to another cell with a different frequency from the cell.

Load balancing (mobility load balancing, MLB) parameters are used to adjust the load of each cell in the same cell group. For example, by configuring MLB parameters, the load balance of each cell in the same sector can be realized, so as to avoid excessive load in some cells, which affects the performance of the entire sector.

Optionally, the network parameter may be a radio frequency (RF) parameter of the cell. By adjusting the RF parameter of the cell, the performance of the cell changes, which may affect the performance of some neighboring cells. Therefore, it is considered that the RF parameters of a cell are network parameters that affect the cell group. By adjusting the RF parameters of a cell in the cell group, the performance of the cell group can be changed. Wherein, the RF parameter of the cell may be the antenna engineering parameter of the site that provides coverage for the cell, for example, the direction angle and inclination angle of the antenna.

The network parameters can also be cell reselection parameters. The cell re-parameter is used to realize the re-access of the terminal equipment in the idle state. For example, when the terminal device is disconnected from the cell A and is in the idle state, the terminal device can reconnect to the cell D according to the cell parameters. The terminal equipment is connected to the port of the cell, and the cell reselection can affect the performance of some neighboring cells. Therefore, the cell reselection parameter is considered to be the network parameter that affects the cell group. The cell group can be changed through the cell reselection parameter. Performance.

(4) Performance indicators of cell groups

In the embodiments of the present application, the performance index of the cell group is used to describe the performance of the cell group. For example, the performance indicators of the cell group may be the average user rate of the cell, the percentage of the edge rate of the cell less than 5M, the key performance indicator (KPI) of the network, and the voice over LTE (Voice over LTE) drop rate. Among them, the network KPI may be the dropped call rate, the access success rate, and so on.

(5) Network parameter recommendation algorithm

In the embodiment of the present application, the network parameter recommendation algorithm is used to describe the correspondence between network parameters, the status information of the cell group, and the performance index of the cell group. The network parameter recommendation algorithm can be expressed as (r1, r2)=(s, a), where s represents the status information of the cell group, and a represents a certain network parameter of each cell in the cell group (for example, the embodiment of this application) The first network parameter), r1, r2 represent the performance index of the cell group. It is understandable that the input of the network parameter recommendation algorithm is the status information of the cell group and a certain network parameter of each cell in the cell group, and the output of the network parameter recommendation algorithm is the performance index of the cell group. The status information of the cell group can be kept unchanged. When the value of the network parameter of the cell changes, the performance index of the cell group is different.

In specific implementation, the network management device can obtain the status information of multiple different cell groups, the network parameters and performance indicators of the cells, and the status information of multiple different cell groups, the network parameters and performance of the cells according to the machine learning model. The indicators are learned to obtain the network parameter recommendation algorithm. Among them, the machine learning model may be a deep learning model, for example, a support vector machine (SVM) model, a random forest (random forest, RF) model, and so on.

In a possible implementation manner, the network management device may determine the state information of at least one cell group;

Learning the state information of the at least one cell group, at least one network parameter, and at least one performance index, and determining the network parameter recommendation algorithm. Wherein, the determining the status information of the at least one cell group includes: for each cell group in the at least one cell group, determining the cell group according to the traffic statistics index of each cell in the cell group Status information of the group.

For example, the network management device can determine the network parameter recommendation algorithm (also called the network parameter recommendation model) through the following three steps:

S1. Determine multiple cell groups.

Specifically, for a certain cell, a cell group including the cell is determined. For example, to determine the same-frequency cells in the neighboring cell of this cell, a cell group can also be determined, including this cell and the first N same-frequency cells with a large number of handovers. Or, to determine the inter-frequency cells in the neighboring cell of the current cell, a cell group can also be determined, including the current cell and the first N inter-frequency cells with a large number of handovers. Or, the cells in a sector constitute a cell group. Among them, N is a settable value.

S2. Obtain the statistical indicators of the cell, and determine the status information of each cell group according to the statistical indicators of the cell.

In specific implementation, the network management device first obtains the statistical indicators of the cell from the network device (for example, the base station), and the statistical indicators include the status information, network parameters, and performance indicators of the cell. The state information of each cell in the cell group can also be calculated to obtain the state information of the cell group.

In a possible implementation, the network management device collects traffic statistics, configuration data, and operation logs and analyzes them. The collected data can also be processed at the granularity of time, including data division, splicing, etc., for example, after processing The data is the traffic statistics indicator within 15 minutes. The processed data includes status information, performance indicators, network parameters, and so on.

Second, determine the status information of the cell group based on the processed data. Specifically, the status information of a cell may be an index of an accumulation type, that is, the status information of the cell group can be obtained by summing the indicators of each cell in the cell group. The status information of a cell can also be a calculation type index, that is, the index of each cell in the cell group is calculated (for example, the numerator and denominator are added) first, and then the status information of the cell group is obtained according to the result of the calculation.

The following uses the cell group as a cluster as an example to illustrate how to obtain the status information of the cell group according to the statistical indicators of the cell:

(1) The status information is an index of accumulation type: add the indicators of each cell in the cluster to obtain the status information of the cluster, for example, the traffic of each cell in the cluster is added to obtain the traffic of the cluster, and the number of users in each cell in the cluster is added The number of users in the cluster is obtained, and the scheduling time of each cell in the cluster is added to obtain the scheduling time of the cluster.

(2) The status information is an index of the calculation type: for the index of each cell in the cluster, the numerator and denominator of the parameters are added to calculate the status information of the cluster. For example, the parameter FULLBUFFER rate relates to the statistical period flow and the scheduling duration, where the statistical period flow is the numerator and the scheduling duration is the denominator. The statistical period traffic corresponding to each cell can be added first to obtain the total statistical period traffic, the scheduling duration corresponding to each cell is accumulated to obtain the total scheduling duration, and the total statistical period traffic is divided by the total scheduling duration to obtain the FULLBUFFER rate of the cluster.

It should be noted that the status information of the cell group can also be marked, for example, the status information of the intra-frequency cluster is marked as NN.IntraC.XXX, and the state information of the inter-frequency cluster is marked as NN.InterC.XXX, sector The status information of the cluster is marked as NN.SectorC.XXX. Among them, the same-frequency cluster, that is, the cells in the cluster, are all cells of the same frequency, the different-frequency cluster, that is, the cells in the cluster, are all inter-frequency cells, and the sector cluster, that is, the cells in the cluster belong to the same sector, and XXX represents the status information parameter .

Table 1 shows some statistical indicators and calculation formulas for calculating these indicators. These calculation formulas are used to obtain the status information of the cell group:

Table 1

Referring to Table 1, A _i is the reference signal receiving power (RSRP) on the physical uplink shared channel (physical uplink shared channel, PUSCH) of the i-th cell in the cell group in a sampling period. Among them, a single terminal device is used as a sampling point, and RSRP is a value measured by a terminal device. b _i is the number of sampling times in the i-th cell in the cell group in a sampling period.

C _i is the path loss value of the UE camped in the i-th cell in the cell group, and D _j is the j-th path loss value greater than the preset threshold. In a possible implementation manner, the path loss values of terminal devices in a radio resource control (radio resource control) connection state in the cell group can be periodically sampled.

E _i is the number of users in the i-th cell in the cell group in a sampling period.

F _i is the data size of the service data unit (SDU) successfully sent by the i-th cell in the cell group in a sampling period.

G _i is the cumulative value of the channel quality indicator (CQI) value reported by each UE camped in the _i-th cell in the cell group; H i is the CQI reported by each UE in the i-th cell in the cell group The cumulative value of the number of times.

G _i is the noise power measured on the i-th cell in the cell group in a sampling period. For example, the noise power can be measured on an uplink physical resource block (PRB).

L _i is the number of cells available downlink PRB group i-th cell; K _i is the number of cells in the i-th cell group actually used in downlink PRB.

P _i is the number of cells available uplink PRB group i-th cell; S _i is the number of cells in the i-th cell group actually used in downlink PRB.

W _i is the sum of the data size of the SDU sent by the i-th cell in the cell group; the number of available uplink PRBs; V _i is the sum of the effective duration of the SDU sent by the i-th cell in the cell group. It should be noted that no calculation is made for the duration of time that is scheduled by the base station but not actually sent data.

The number of available uplink PRB;; Q _i is the cell group SDU is transmitted, the throughput is less than 5Mbps on the cumulative number of the i-th cell is transmitted SDU _i T cell groups on the i-th cell, throughput statistics The total number of times.

S3. Learning the network parameters, the status information of the cell group, and the performance index of the cell group, and determining the network parameter recommendation algorithm.

Specifically, the machine learning model learns network parameters, status information of the cell group, and performance indicators of the cell group to obtain a network parameter recommendation algorithm. The network parameter recommendation algorithm can be described as: r=f(s,a).

Among them, r is the performance index of the cell group. This algorithm supports simultaneous modeling and prediction of multiple targets. It is understandable that the output of the network parameter recommendation algorithm can be multiple performance indicators. For example, (r ₁ , r ₂ )=f(s, a).

s is the status information of the cell group, which can include multiple indicators, such as the number of users, traffic, and CQI.

a is a network parameter, which can be a cell system parameter, intra-frequency handover, inter-frequency handover, sector load balancing, etc. The network parameter can also include multiple. For example, assuming that the cluster includes 5 cells, a may include 5 values, which are the intra-frequency handover parameters P1, P2, P3, P4, and P5 of the 5 cells.

f represents the model relationship between the network parameter a and the state information s of the cell group and the performance index r of the cell group.

The parameter a can be or can be a system parameter that affects the cell.

The embodiment of the present application provides a network parameter adjustment method, which is applied to the network management device in FIG. 1. As shown in FIG. 6, the method includes the following steps:

601. Determine status information of a first cell group; wherein the status information is used to indicate a traffic statistics index of the first cell group, the first cell group includes at least two cells, and the Performance affects each other.

In specific implementation, the network management device may determine the state information of the first cell group by the first cell group according to the traffic statistics index of each of the at least two cells included in the first cell group. Among them, the traffic statistics index of the cell may be the counter index of the cell, for example, the number of users and traffic of the cell.

In a possible implementation manner, the traffic statistics index of each cell in the first cell group may be calculated to obtain the state information of the first cell group. For example, the traffic statistics indicators of each cell in the first cell group are summed to obtain the state information of the first cell group.

It should be noted that the cells in the first cell group may be intra-frequency cells or inter-frequency cells, the first cell group is a sector, or the first cell group is an SFN area. It is understandable that at least two cells in the first cell group are intra-frequency cells or inter-frequency cells, or, the at least two cells are inter-frequency cells, or, the at least two cells belong to the same sector , Or, at least two cells belong to the same SFN area.

602. Determine the target value of the first network parameter of each cell in the first cell group according to the state information of the first cell group and a network parameter recommendation algorithm; the network parameter recommendation algorithm is used to describe the state information , The corresponding relationship between the network parameters and the performance indicators of the first cell group, when the value of the first network parameter of each cell is the corresponding target value, the first performance of the first cell group The index is the best.

It should be noted that the first network parameter is any one of the following parameters: cell system parameters, intra-frequency cell switching thresholds, inter-frequency cell switching thresholds, or load balancing parameters. It is understandable that the network parameter recommendation algorithm can determine the performance indicators of the cell group under different cell state information and network parameters. The value of the network parameter and the performance index of the cell group are different. By adjusting the value of the network parameter, the best performance index can be obtained.

In specific implementation, first determine the performance index r that needs to be optimized, and then determine the state information of the first cell group and the network parameters to be adjusted, for example, the first network parameters described in the embodiment of the present application. The network parameter recommendation algorithm can predict the performance index r that can be obtained by adjusting the network parameter a under a certain state information s. Therefore, if the value of the first network parameter is different, and the first performance index is different, the value that makes the first performance index the best can be filtered out, that is, the target value described in the embodiment of the present application.

In the embodiment of the present application, the values of the first network parameters of each cell in the cell group need to be integrated to obtain the best performance index. The target value of the first network parameter of each cell may be the same or different, which is not limited in the embodiment of the present application. For each cell in the first cell group, the target value corresponding to one of the cells is determined first, and the values of the first network parameters of the remaining cells are default values. Subsequently, the value of the first network parameter of the cell is fixed, and the value of the first network parameter of another cell is adjusted. Iterate until a set of values that makes the cell group performance index the best is selected.

Specifically, the first target value corresponding to the i-th cell in the first cell group is determined according to the network parameter recommendation algorithm. For the i-th cell in the first cell group, all candidate values of the first network parameter may be traversed to obtain different first performance indicators. It is also possible to filter out the value that makes the first performance index the best, that is, the target value corresponding to the i-th cell. It should be noted that the value of the first network parameter of the remaining cells in the first cell group except the i-th cell is a default value, and the first network parameter of the i-th cell Is the first performance index of the first cell group when the value of is the first target value, and the value of the first network parameter is higher than the value of the first network parameter of the i-th cell when the remaining candidate values are the first cell The first performance index of the group; the i is an integer greater than or equal to 1.

It is also possible to fix the value of the first network parameter of the i-th cell at the corresponding target value, and continue to determine the target value of the first network parameter of other cells. For example, the second target value corresponding to the i+1th cell in the first cell group is determined according to the network parameter recommendation algorithm; the first network of the first i cell in the first cell group The value of the parameter is the corresponding target value, the value of the first network parameter of the remaining cells in the first cell group except the first i cell is the default value, and the value of the i+1th cell is the default value. The first performance index of the first cell group when the value of the first network parameter is the second target value and the value of the first network parameter of the first i cell is the corresponding target value, When the value of the first network parameter of the i+1th cell is higher than the remaining candidate values and the value of the first network parameter of the first i cell is the corresponding target value, the first cell The first performance indicator of the group.

It should be noted that the default value of the first network parameter may be one of the candidate values of the first network parameter, and the default value of the first network parameter of different cells may be the same or different, which is not limited in this embodiment of the application. .

For example, the first cell group includes cell A, cell B, and cell C. The candidate values of the first network parameter include x ₁ , x ₂ , x ₃ , x ₄ , and x ₅ , where x ₃ is the default value. First, the first network parameters of cell A take x ₁ , x ₂ , x ₃ , x ₄ , x ₅ in sequence, the first network parameters of cell B are fixed to x ₃ , and the first network parameters of cell C are fixed to x ₃ . Set the state information s of the first cell group and the network parameters a=(x ₁ , x ₃ , x ₃ ), (x ₂ , x ₃ , x ₃ ), (x ₃ , x ₃ , x ₃ ), (x ₄ , x ₃ , x ₃ ), (x ₅ , x ₃ , x ₃ ), the first performance index obtained in turn is: r ₁ , r ₂ , r ₃ , r ₄ , r ₅ . Among them, r _{2 is the} largest, and the target value of the first network parameter of cell A is x ₂ .

The first network parameter of the fixed cell A is x ₂ , the first network parameter of the cell C is fixed to x ₃ , and the first network parameter of the cell B is x ₁ , x ₂ , x ₃ , x ₄ , x ₅ , and the State information s and network parameters a of a cell group = (x ₂ , x ₁ , x ₃ ), (x ₂ , x ₂ , x ₃ ), (x ₂ , x ₃ , x ₃ ), (x ₂ , x ₄ , x ₃ ), (x ₂ , x ₅ , x ₃ ), the first performance index obtained in turn is: r ₆ , r ₇ , r ₈ , r ₉ , and r ₁₀ . Among them, r _{9 is the} largest, and r _{9 is} greater than r ₂ , then the target value of the first network parameter of cell B is x ₄ .

The first network parameter of fixed cell A is x ₂ , the first network parameter of fixed cell B is x ₄ , the first network parameter of cell C is fixed to x ₃ , and the first network parameter of cell C is x ₁ and x _{2 in turn} , X ₃ , x ₄ , x ₅ , the state information s of the first cell group and the network parameters a=(x ₂ , x ₄ , x ₁ ), (x ₂ , x ₄ , x ₂ ), (x ₂ , X ₄ , x ₃ ), (x ₂ , x ₄ , x ₄ ), (x ₂ , x ₄ , x ₅ ), the first performance index obtained in turn is: r ₁₁ , r ₁₂ , r ₁₃ , r ₁₄ , R ₁₅ . Among them, r _{15 is the} largest, and r _{15 is} greater than r ₉ and r ₂ , then the target value of the first network parameter of cell C is x ₅ .

Then when the first network parameter of cell A is x ₂ , the first network parameter of cell B is x ₄ , and the first network parameter of cell C is x ₅ , the first performance index of the first cell group is the best, which is The first network parameters recommended by the first cell group are x ₂ , x ₄ , and x ₅ .

Optionally, the network management device may send the target value of the first network parameter to the network device (for example, the base station), so that the network device can adjust the value of the first network parameter according to the target value of the first network parameter to optimize the first cell group The performance of the group.

In the case of dividing each functional module corresponding to each function, FIG. 7 shows a possible schematic structural diagram of the network management device involved in the foregoing embodiment. The network management device shown in FIG. 7 may be the network management device described in the embodiment of the present application, or may be a component of the network management device that implements the foregoing method. As shown in FIG. 7, the network management device includes a parameter processing unit 701, a parameter recommendation unit 702, and a transceiver unit 703. The processing unit may be one or more processors, and the transceiver unit 703 may be a network interface.

The parameter processing unit 701 is configured to obtain statistical indicators of the cell, for example, to support the network management device to perform step 601, and/or other processes used in the technology described herein.

The parameter recommendation unit 702 is configured to recommend optimized network parameters of the cell to improve the performance of the cell group, for example, to support the network management device to perform step 601 and/or other processes used in the technology described herein.

The transceiver unit 703 is configured to support, for example, communication between the network management device and other devices, for example, to support the network management device to send the target value of the first network parameter to the network device, and/or other processes used in the technology described herein.

In a possible implementation manner, the network management device shown in FIG. 7 may also be a network management device or a chip used in a network management device. The chip may be a System-On-a-Chip (SOC).

Wherein, the above transceiver unit 702 for receiving/sending may be a network interface of the network management device for receiving signals from other network management devices.

Exemplarily, in the case of using an integrated unit, a schematic structural diagram of a network management device provided in an embodiment of the present application is shown in FIG. 8. In FIG. 8, the network management device includes: a processing module 801 and a communication module 802. The processing module 801 is used to control and manage the actions of the network management device, for example, to perform the steps performed by the parameter processing unit 701 and the parameter recommendation unit 702 described above, and/or to perform other processes of the technology described herein. The communication module 802 is configured to perform the steps performed by the above-mentioned transceiver unit 703, and support the interaction between the network management device and other devices, such as interaction with other network devices. As shown in FIG. 8, the network management device may further include a storage module 803, and the storage module 803 is used to store program codes and data of the network management device.

When the processing module 801 is a processor, the communication module 802 is a network interface, and the storage module 803 is a memory, the network management device is the network management device shown in FIG. 2.

This application provides a computer-readable storage medium in which computer instructions are stored. The computer instruction instructs the network management device to execute the above-mentioned network parameter recommendation method, or the computer instruction is used to implement the functional units included in the network management device.

This application provides a computer program product. The computer program product includes computer instructions. The computer instruction instructs the network management device to execute the above-mentioned network parameter recommendation method, or the computer instruction is used to implement the functional units included in the network management device.

Through the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and brevity of the description, only the division of the above-mentioned functional modules is used as an example for illustration. In practical applications, the above-mentioned functions can be allocated according to needs. It is completed by different functional modules, that is, the internal structure of the database access device is divided into different functional modules to complete all or part of the functions described above.

In the several embodiments provided in this application, it should be understood that the disclosed database access device and method can be implemented in other ways. For example, the embodiments of the database access device described above are only illustrative. For example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or The components can be combined or integrated into another device, or some features can be omitted or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, database access devices or units, and may be in electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate. The parts displayed as units may be one physical unit or multiple physical units, that is, they may be located in one place, or they may be distributed to multiple different places. . Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

In addition, the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application are essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product, and the software product is stored in a storage medium. It includes several instructions to make a device (may be a single-chip microcomputer, a chip, etc.) or a processor execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

The above are only specific implementations of this application, but the protection scope of this application is not limited to this. Any changes or substitutions within the technical scope disclosed in this application shall be covered by the protection scope of this application. . Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

A method for adjusting network parameters, characterized in that the method includes:

Determine the status information of the first cell group; wherein, the status information is used to indicate the traffic statistics index of the first cell group, the first cell group includes at least two cells, and the performance of the at least two cells is mutually related. influences;

The target value of the first network parameter of each cell in the first cell group is determined according to the state information of the first cell group and the network parameter recommendation algorithm; the network parameter recommendation algorithm is used to describe the state information, network The corresponding relationship between the parameters and the performance indicators of the first cell group. When the value of the first network parameter of each cell is the corresponding target value, the first performance indicator of the first cell group is the best good.
The method according to claim 1, wherein the determining the status information of the first cell group comprises:

The state information of the first cell group is determined according to the traffic statistics index of each of the at least two cells.
The method according to claim 1 or 2, wherein the first network parameter of each cell in the first cell group is determined according to the state information of the first cell group and a network parameter recommendation algorithm The target value of includes:

Determine the first target value corresponding to the i-th cell in the first cell group according to the network parameter recommendation algorithm; the values of the remaining cells in the first cell group except the i-th cell The value of the first network parameter is the default value, and the value of the first network parameter of the i-th cell is the first performance index of the first cell group when the first target value is higher than the The value of the first network parameter of the i-th cell is the first performance index of the first cell group when the remaining candidate values are used; the i is an integer greater than or equal to 1;

Determine the second target value corresponding to the i+1th cell in the first cell group according to the network parameter recommendation algorithm; the value of the first network parameter of the first i cell in the first cell group The value is the corresponding target value, the value of the first network parameter of the remaining cells in the first cell group except the first i cell is the default value, and the value of the i+1th cell When the value of the first network parameter is the second target value and the value of the first network parameter of the first i cells is the corresponding target value, the first performance index of the first cell group is higher than When the value of the first network parameter of the i+1th cell is the remaining candidate values and the value of the first network parameter of the first i cell is the corresponding target value, the first cell group The first performance index.
The method according to any one of claims 1-3, wherein the method further comprises:

Determine the status information of at least one cell group;

Learning the state information of the at least one cell group, at least one network parameter, and at least one performance index, and determining the network parameter recommendation algorithm.
The method according to claim 4, wherein said determining the state information of at least one cell group comprises:

For each cell group in the at least one cell group, the state information of the cell group is determined according to the traffic statistics index of each cell in the cell group.
The method according to any one of claims 1-5, wherein the first network parameter is any one of the following parameters:

Cell system parameters, intra-frequency cell handover threshold, inter-frequency cell handover threshold or load balancing parameters.
The method according to any one of claims 1-6, wherein the at least two cells are intra-frequency cells, or, the at least two cells are inter-frequency cells, or, the at least two cells are They belong to the same sector, or the at least two cells belong to the same single-frequency networking SFN area.
A network management device, characterized in that it comprises:

The parameter processing unit is configured to determine the state information of the first cell group; wherein the state information is used to indicate the traffic statistics index of the first cell group, the first cell group includes at least two cells, and the at least The performance of the two cells influence each other;

The parameter recommendation unit is configured to determine the target value of the first network parameter of each cell in the first cell group according to the state information of the first cell group and a network parameter recommendation algorithm; the network parameter recommendation algorithm uses In describing the correspondence between the status information, network parameters, and performance indicators of the first cell group, when the value of the first network parameter of each cell is the corresponding target value, the first cell group The first performance index is the best.
The network management device according to claim 8, wherein the parameter processing unit is specifically configured to determine the state information of the first cell group according to the traffic statistics index of each of the at least two cells.
The network management device according to claim 8 or 9, wherein the parameter recommendation unit is specifically configured to determine, according to the network parameter recommendation algorithm, the ith cell corresponding to the i-th cell in the first cell group A target value; the value of the first network parameter of the remaining cells in the first cell group except the i-th cell is the default value, and the value of the first network parameter of the i-th cell When the value is the first target value, the first performance index of the first cell group, and when the value of the first network parameter of the i-th cell is higher than the remaining candidate values, the first cell group The first performance index of the group; the i is an integer greater than or equal to 1;

Determine the second target value corresponding to the i+1th cell in the first cell group according to the network parameter recommendation algorithm; the value of the first network parameter of the first i cell in the first cell group The value is the corresponding target value, the value of the first network parameter of the remaining cells in the first cell group except the first i cell is the default value, and the value of the i+1th cell When the value of the first network parameter is the second target value and the value of the first network parameter of the first i cells is the corresponding target value, the first performance index of the first cell group is higher than When the value of the first network parameter of the i+1th cell is the remaining candidate values and the value of the first network parameter of the first i cell is the corresponding target value, the first cell group The first performance index.
The network management device according to any one of claims 8-10, wherein the parameter recommendation module is further configured to determine state information of at least one cell group;

Learning the state information of the at least one cell group, at least one network parameter, and at least one performance index, and determining the network parameter recommendation algorithm.
The network management device according to claim 11, wherein the parameter recommendation unit is specifically configured to: for each cell group in the at least one cell group, according to each cell group in the cell group The traffic statistics index determines the status information of the cell group.
The network management device according to any one of claims 8-12, wherein the first network parameter is any one of the following parameters:

Cell system parameters, intra-frequency cell handover threshold, inter-frequency cell handover threshold or load balancing parameters.
The network management device according to any one of claims 8-13, wherein the at least two cells are same-frequency cells, or, the at least two cells are different-frequency cells, or, the at least two cells are Two cells belong to the same sector, or the at least two cells belong to the same single frequency networking SFN area.
A network management device, wherein the network management device includes a processor and a memory; when the processor executes computer instructions in the memory, the network management device executes any of claims 1 to 7 The method described in one item.
A computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, which when executed, cause a computer to execute the method according to any one of claims 1 to 7.