Visual network optimization method, device, equipment and system

Abstract

The embodiment of the present invention relates to the field of network optimization technology, and discloses a visual network optimization method, device, equipment and system, the method comprising: obtaining the current location information of the network optimization client, and sending the current location information to the simulation system; receiving the simulation result information generated by the simulation system according to the current location information; tracking the real-time target location of the network optimization client through the simulation result information, and determining the virtual location information of the network optimization client in the simulation system according to the real-time target location information; if the current location information is consistent with the virtual location information, rendering the simulation result information. Through the above method, the efficiency of network optimization is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of network optimization, and in particular to a visual network optimization method, device, equipment and system. Background Art

[0002] 5G network construction is an important national strategy in my country. Currently, 5G base stations have been built on a large scale. The high reliability, low latency and large bandwidth of 5G networks have brought extremely fast user experience. AR technology has also developed rapidly under the background of 5G. AR technology can not only display real-world information, but also virtual information at the same time. The two types of information complement and overlap each other, and users can get a satisfactory immersive experience. Signals are invisible and intangible. If VR technology is used to visualize signals and then applied to network operation and optimization, it will greatly improve user perception, while improving network optimization effects and reducing operation and maintenance costs.

[0003] At present, network operation and optimization are mainly carried out through analysis of large amounts of monitoring data, performance data, network management data, etc., and then judged by experienced engineers and solutions are proposed. This method cannot truly feel the existence of the signal, the user experience is poor, and the effect of network optimization and adjustment takes a long time to show. Summary of the invention

[0004] In view of the above problems, the embodiments of the present invention provide a visual network optimization method, apparatus, device and system for solving the problem of low network optimization efficiency in the prior art.

[0005] According to one aspect of an embodiment of the present invention, a visual network optimization method is provided, which is applied to a network optimization client, and the method includes:

[0006] Acquire the current location information of the network optimization client, and send the current location information to the simulation system;

[0007] Receiving simulation result information generated by the simulation system according to the current position information;

[0008] Tracking the real-time target location of the network optimization client through the simulation result information, and determining the virtual location information of the network optimization client in the simulation system according to the real-time target location information;

[0009] If the current position information is consistent with the virtual position information, the simulation result information is rendered.

[0010] Tracking the real-time target position of the network optimization client through the simulation result information further includes:

[0011] The real-time target position of the network optimization client is determined according to the simulation result through three-dimensional tracking and registration technology.

[0012] The method further includes: if the current location information is inconsistent with the virtual location information, reacquiring the current location information of the network optimization client, and sending the current location information to the simulation system to generate new simulation result information.

[0013] The simulation result information includes regional bottom layer information and regional height information;

[0014] The rendering of the simulation result information includes:

[0015] Performing data processing on the regional bottom layer information and the regional height layer information in the simulation result information;

[0016] Determine color information corresponding to the signal level value in the simulation result information;

[0017] The region bottom layer and the region height layer are three-dimensionally rendered according to the color information.

[0018] After rendering the simulation result information, the method further includes:

[0019] Determine whether there is a weak coverage area according to the rendered simulation result information;

[0020] If there is a weak coverage area, after adjusting the working parameters in the weak coverage area, the adjusted working parameters are sent to the simulation system so that the simulation system regenerates simulation result information.

[0021] After the current position information is sent to the simulation system, the method further comprises:

[0022] The simulation system searches for base stations according to the current location information, determines grid information corresponding to the coverage range of the base stations according to the searched base station information, and sends the grid information as simulation result information to the network optimization client.

[0023] The present application also provides a visual network optimization device, including:

[0024] Position information acquisition module: used to acquire current position information and send the current position information to the simulation system;

[0025] A simulation result information receiving module: used for receiving simulation result information generated by the simulation system according to the current position information;

[0026] Simulation result information confirmation module: used to track the real-time target position of the network optimization client through the simulation result information, and determine the virtual position information of the network optimization client in the simulation system according to the real-time target position information; confirm whether the current position information is consistent with the virtual position information;

[0027] Visualization rendering module: used for rendering the simulation result information when the current position information is consistent with the virtual position information.

[0028] The embodiment of the present application also proposes a network optimization terminal, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus;

[0029] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the above-mentioned visual network optimization method.

[0030] The embodiment of the present application further proposes a computer-readable storage medium, in which at least one executable instruction is stored. When the executable instruction is executed on a network optimization terminal, the network optimization terminal executes the above-mentioned visualized network optimization method.

[0031] The embodiment of the present application also proposes a visual network optimization system, which includes the above-mentioned visual network optimization device and simulation system.

[0032] The above-mentioned embodiment of the present application applies the simulation system to the network optimization system, and renders the simulation results by judging whether the virtual location information of the user in the simulation system is consistent with the actual location information of the network optimization client, thereby ensuring the accuracy of the simulation results and greatly improving the efficiency of network optimization.

[0033] The above description is only an overview of the technical solution of the embodiment of the present invention. In order to more clearly understand the technical means of the embodiment of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present invention more obvious and easy to understand, the specific implementation mode of the present invention is specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0035] Figure 1 A schematic diagram of a visualized network optimization process provided by an embodiment of the present invention is shown;

[0036] Figure 2A schematic diagram of the workflow of a visual network simulation system provided by an embodiment of the present invention is shown;

[0037] Figure 3 A schematic diagram of a visualized network optimization process provided by another embodiment of the present invention is shown;

[0038] Figure 4 A schematic diagram of network optimization adjustment provided by an embodiment of the present invention is shown;

[0039] Figure 5 A structural diagram of a visual network optimization device provided by an embodiment of the present invention is shown;

[0040] Figure 6 A structure diagram of a visual network optimization system provided by an embodiment of the present invention is shown;

[0041] Figure 7 The diagram shows a structure diagram of a network optimization terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0043] With the popularization of 5G networks and the increasing maturity of AR technology, AR technology improves the experience of AR technology by utilizing the high speed, low latency and high reliability of 5G networks, thereby improving the positioning capability of AR terminals and user perception. The embodiment of this application is a network optimization method, device, equipment and system based on visualization technology proposed under the above technical background. By applying AR technology to the field of network optimization, the difficulty of network optimization is reduced and the experience of network optimization is improved.

[0044] The visualization network optimization method proposed in the implementation of the present application is applied to a visualization network optimization client. The visualization network optimization client can be a dedicated network optimization terminal or an ordinary mobile phone. A dedicated network optimization APP is installed on the mobile phone or the network optimization terminal. Through the APP, the network optimization terminal can be connected to the simulation system, obtain simulation data, and display the simulation data in 3D on the APP. Network optimization staff can easily view the coverage of the wireless network. The simulation system is usually a server with a simulation model installed. The simulation data information of the network to be optimized is pre-stored on the server to restore the actual coverage of the network to be optimized to the greatest extent.

[0045] Specifically, Figure 1As shown, a schematic diagram of a visual network optimization process provided by an embodiment of the present invention is shown, and the method is executed by a network optimization client. Figure 1 As shown, the method comprises the following steps:

[0046] Step 100: Acquire the current location information of the network optimization client, and send the current location information to the simulation system;

[0047] The network optimization client obtains its current location information through its own GPS module, the location information includes longitude information and latitude information, and sends the location information to the simulation system. The simulation system is usually set up in a remote server and is a simulation model established in advance according to network scenario information.

[0048] Step 200: receiving simulation result information generated by the simulation system according to the current position information;

[0049] In network optimization, the orientation of AR visualization corresponding to different scenes is different. For example, in the city center, the simulation coverage accuracy is often set relatively high in the simulation system, while in the suburbs, the simulation coverage longitude is often set relatively low. Therefore, when the simulation system receives the current location information sent by the network optimization client, it will determine the corresponding scene according to the current location information of the network optimization client, and call different simulation models according to different scenes.

[0050] The simulation system searches for base station information within the corresponding range according to the simulation model, marks the grid information of the base station coverage according to the global cell identification code CGI (Cell Global Identifier) ​​information of the base station and the coverage prediction calculation results, and counts the grid-level results of the base station coverage prediction under the CGI, and sends the prediction results as simulation results to the network optimization client.

[0051] Step 300: Tracking the real-time target position of the network optimization client through the simulation result information, and determining the virtual position information of the network optimization client in the simulation system according to the real-time target position information;

[0052] After the network optimization client receives the simulation result information, in order to ensure the consistency between the location information of the network optimization client and the location information in the simulation result information, the network optimization client uses the three-dimensional tracking and registration technology through the simulation result information to track the real-time target position of the network optimization client and determine the virtual location information of the network optimization client in the simulation system.

[0053] Step 400: If the current position information is consistent with the virtual position information, the simulation result information is rendered.

[0054] The network optimization client determines whether the virtual location information is consistent with the current location information of the network optimization client. If they are consistent, it means that there is no problem with the location information generated in the simulation system, and the simulation result is rendered.

[0055] The above-mentioned embodiment of the present application applies the simulation system to the network optimization system, and renders the simulation results by judging whether the virtual location information of the user in the simulation system is consistent with the actual location information of the network optimization client, thereby ensuring the accuracy of the simulation results and greatly improving the efficiency of network optimization.

[0056] In the above embodiment, before the implementation of the visual network optimization method, the simulation system needs to be pre-set, and the simulation system is often set on a remote server. The simulation system includes multiple simulation models, and each simulation model needs to be established in advance by coverage prediction. Specifically, the present application also proposes a schematic diagram of a workflow of a visual network simulation system, as shown in FIG. Figure 2 As shown, including:

[0057] Step 101: Determine a network optimization area;

[0058] When it is necessary to optimize the network in a certain area, it is necessary to determine the network area to be optimized in advance, and the simulation system creates or imports polygonal area data of the network optimization area according to the simulation requirements. For example, if it is necessary to simulate the area of ​​a street in a city, it is necessary to import the information of the area, such as the area range information, into the simulation system in advance.

[0059] Step 102: Acquire the working parameters of wireless base stations in the network optimization area;

[0060] According to the information of the network optimization area, the working parameters of the wireless base stations that meet the conditions are queried in the database of the simulation system. For example, according to the longitude and latitude information of the network optimization area, the base stations falling within this range are determined. At the same time, according to the standard of the base station to be optimized, the wireless base stations that meet the conditions are determined, and the working parameter data of the wireless base stations that meet the conditions are obtained from the data of the simulation system.

[0061] Step 103: Determine whether the wireless base station used for simulation is consistent with the existing network;

[0062] Since the wireless base station engineering parameters will directly affect the simulation results, in order to ensure that the simulation results are consistent with the actual wireless signals of the existing network as much as possible, it is necessary to verify the engineering parameters through the existing network MDT data, drive test data or on-site survey, etc., to determine whether the simulation engineering parameters are consistent with the actual engineering parameters. If they are consistent, go to step 105; if not, go to step 104.

[0063] Step 104: Correct the wireless base station working parameters.

[0064] When it is found that the working parameters are inconsistent with the actual wireless signal, the working parameters of the wireless base station are corrected, and it is cyclically determined whether the corrected working parameters are consistent with the existing network to ensure that the simulated working parameters are as close as possible to the working parameters of the existing network.

[0065] Step 105: parsing Plannet electronic map information of the simulation area;

[0066] The three-dimensional high-precision Plannet electronic map can reflect the city's landforms and topography. In this step, the digital elevation, ground coverage, line map, point feature annotation, building distribution and vector building distribution models of the existing electronic map are imported into the simulation system database to analyze and render the environment of the optimization area.

[0067] Step 106: Determine a three-dimensional wireless signal propagation path;

[0068] The simulation system matches the wireless signal propagation environment according to the type of wireless base station cell, the topography of the simulation area, etc., and completes the search for the wireless signal propagation path in three-dimensional space based on the principles of geometric optics and using ray tracing search algorithms, so as to simulate the propagation mode of wireless signals in the real environment to the greatest extent.

[0069] Step 107: Calculate the three-dimensional space wireless signal propagation path loss;

[0070] For each propagation path, the path loss of each path is calculated according to the loss of different propagation environments and the attenuation of radio signals. After cyclically calculating the path losses of all paths, the final path loss of the cell is synthesized.

[0071] Step 108: Calculate the grid-level field strength value of the three-dimensional wireless signal;

[0072] According to the transmission power in the wireless base station parameters obtained in the above steps, the fading margin and feeder loss set by the simulation platform, etc., the grid-level field strength value of the wireless signal in the three-dimensional space is synthesized. The cell-level wireless signal field strength values ​​are arranged and combined, and the maximum field strength value in the same grid is taken as the final field strength value of the grid, and the final field strength value is output.

[0073] Step 109: The simulation system outputs simulation result information;

[0074] The simulation system simulates the network optimization area according to the final field strength value and outputs simulation result information.

[0075] The above-mentioned embodiment of the present application uses three-dimensional ray tracing technology to simulate and calculate the existing 5G wireless network signal to ensure the accuracy of the wireless network signal calculation in the virtual world. Based on the principle of geometric optics, three-dimensional ray tracing simulates and searches for the reflection, diffraction, transmission and other paths of wireless signal propagation, fully considering the path loss caused by objects, landforms, interference, etc. during the signal propagation process, and can more accurately calculate the level value of the wireless network signal. Through the above-mentioned visual network simulation system working method, a simulation model for different network optimization areas can be established, and the above-mentioned areas can be simulated and simulated, and the simulation result information can be output, thereby improving the efficiency of network optimization.

[0076] After the above-mentioned visual network simulation system is set up, the visual network optimization method performs network optimization simulation through the simulation system. Specifically, Figure 3 As shown, including:

[0077] Step 301: The network optimization client obtains current location information;

[0078] The network optimization client obtains the latitude and longitude information of the current location by calling GPS positioning. The GPS positioning is a general term, including but not limited to global satellite positioning information GPS, Beidou positioning system and other positioning systems.

[0079] Step 302: The network optimization client calls the simulation system interface to report the current location information;

[0080] In practice, different scenes require different ranges of AR visualization. The network optimization client reports the current location information by calling the API interface of the simulation system according to the real scene and longitude and latitude information of the current location to obtain simulation results near the center point in different scenes.

[0081] Step 303: The simulation system determines the base station information according to the reported current location information;

[0082] The simulation system searches for base stations within a corresponding range according to current location information.

[0083] Step 304: The simulation system marks the grid information covered by the base station in the simulation result according to the CGI information;

[0084] The simulation system marks the grids covered by the base station according to the CGI information of the base station and the coverage prediction calculation results, and counts and assembles the grid-level results of the base station coverage prediction under the CGI.

[0085] Step 305: The network optimization client receives the simulation result information and determines the virtual location information in the simulation system;

[0086] After the network optimization client receives the simulation result information, in order to ensure the consistency between the location information of the network optimization client and the location information in the simulation result information, the network optimization client uses the three-dimensional tracking and registration technology through the simulation result information to track the real-time target position of the network optimization client and determine the virtual location information of the network optimization client in the simulation system.

[0087] Step 306: Determine whether the current location information is consistent with the virtual location information;

[0088] If they are not consistent, go to step 301 to reacquire the current location information. If they are consistent, go to step 307.

[0089] Step 307: The network optimization client renders the simulation results;

[0090] After receiving the simulation results, the network optimization client performs preprocessing on the simulation results before use, completes data processing of the regional bottom layer and the regional height layer based on the simulation results, and processes different signal level values ​​according to a preset legend to complete the one-to-one correspondence between the signal level value interval and the color; wherein the preset legend refers to a mapping relationship between a preset level value and a color, for example: a high signal level value is represented by a darker color such as red, and an area with a low signal level value is represented by a lighter color such as yellow, etc.

[0091] The Unity 3D engine is used to render the simulation results in three dimensions, and the two-dimensional data of the regional bottom layer and the regional height layer are rendered in three dimensions. By rendering the simulation results in three dimensions, the visualization of the simulation results is increased.

[0092] Step 308: Using virtual-real combination technology to overlay the simulation rendering result onto the real environment;

[0093] The network optimization terminal superimposes the real environment and simulation data through virtual combination technology to complete the AR visualization display of 5G network signals.

[0094] As can be seen from the above, the above embodiment uses three-dimensional technology to render the simulation results, which shows the transmission status of the network very realistically and vividly, and can efficiently optimize the network. The three-dimensional ray tracing simulation results are used to approximate the actual signals of the existing network, and the simulation results are rendered in three dimensions using the Unity 3D engine to complete the construction of the virtual world of the 5G wireless network signal. The positioning technology and three-dimensional tracking registration technology are used to complete the construction of the real world. Finally, the virtual and real combination module completes the fusion and superposition of the virtual world and the real world. Based on AR technology, the 5G wireless signal that has been "invisible and intangible" is visualized.

[0095] Furthermore, after the rendering of the simulation results is completed, the embodiment of the present application also proposes a process step for optimizing and adjusting the network based on the rendering results, such as Figure 4 As shown, including:

[0096] Step 501: presenting the wireless network signal quality within the field of view of the network optimization client;

[0097] Based on the rendering effect of the above embodiment, the azimuth information of the network optimization client is obtained to present the wireless network signal quality within the field of view of the network optimization client.

[0098] Step 502: Determine whether there is a weak coverage area or a hot spot area;

[0099] If there is no weak coverage area or hot spot area within the field of view, the process ends without any optimization of the area. Otherwise, go to step 503.

[0100] The above-mentioned weak coverage area or hot spot area can be judged by intuitive color, and the user can intuitively understand whether there is a weak coverage area or a hot spot area through the AR simulation effect diagram. Of course, the simulation system can also give users prompts by setting weak coverage reminders or hot spot area reminders.

[0101] Step 503: Adjusting the working parameters of the weak coverage area or the hot spot area;

[0102] If there are weak coverage areas or hot spots, intuitive engineering parameter adjustments can be made in the weak coverage areas or hot spots, including adjusting antenna transmission power, hanging height, azimuth angle, and adding base stations.

[0103] Step 504: the network optimization client reports the adjusted working parameters to the simulation system;

[0104] After completing the adjustment of the working parameters, the network optimization client reports the adjusted working parameters by calling the API interface provided by the simulation platform.

[0105] Step 505: The simulation system simulates the adjusted network and sends the simulation result information to the network optimization client;

[0106] The simulation system simulates the adjusted network and initiates the simulation demand after this adjustment.

[0107] Step 506: the network optimization client re-renders the simulation results;

[0108] The wireless signal is AR displayed in the manner described in the above embodiment.

[0109] Step 507: Determine whether the wireless signal coverage meets the standard;

[0110] If the standard is not met, the process goes to step 503 to continue adjusting the network; if the standard is met, the process goes to step 508.

[0111] Step 508: Save and report the optimized network parameters;

[0112] The network optimization client reports the optimized network working parameters to the simulation system.

[0113] As can be seen from the above, the previous network operation and optimization required the analysis of a large amount of monitoring data, performance data, network management data and other data, and required engineers with certain network experience to make judgments and provide solutions, which cost a lot of manpower and material resources. In this application, through the above-mentioned visual network optimization process, it is possible to quickly and intuitively judge the weak coverage and hot spots of the network, adjust the working parameters and base stations in time, and verify the effect of operation and optimization, which greatly reduces the cost and difficulty of network operation and optimization, and shortens the cycle of network operation and optimization.

[0114] Therefore, in summary, the visualized network optimization method proposed in the embodiment of the present application greatly improves the efficiency of network optimization and shortens the cycle of network operation and optimization by simulating the wireless network and performing AR rendering on the simulation results.

[0115] The present application embodiment proposes a visual network optimization device 600, such as Figure 5 As shown, the device 600 includes: a position information acquisition module 601, a simulation result information receiving module 602, a simulation result information confirmation module 603 and a visualization rendering module 604.

[0116] The position information acquisition module 601 is used to acquire current position information and send the current position information to the simulation system;

[0117] The simulation result information receiving module 602 is used to receive the simulation result information generated by the simulation system according to the current position information;

[0118] The simulation result information confirmation module 603 is used to track the real-time target position of the network optimization client through the simulation result information, and determine the virtual position information of the network optimization client in the simulation system according to the real-time target position information; confirm whether the current position information is consistent with the virtual position information;

[0119] The visualization rendering module 604 is used to render the simulation result information when the current position information is consistent with the virtual position information.

[0120] Furthermore, the simulation result information confirmation module 603 is also used to determine the real-time target position of the network optimization client through three-dimensional tracking and registration technology according to the simulation results; if the current position information is inconsistent with the virtual position information, the current position information of the network optimization client is re-acquired, and the current position information is sent to the simulation system to generate new simulation result information.

[0121] Furthermore, the visualization rendering module 604 is also used to perform data processing on the regional bottom layer information and the regional height layer information in the simulation result information; determine the color information corresponding to the signal level value in the simulation result information; and perform three-dimensional rendering on the regional bottom layer and the regional height layer according to the color information.

[0122] The visual network optimization device provided in the above-mentioned embodiment of the present application applies the simulation system to the network optimization system, and renders the simulation results by judging whether the virtual location information of the user in the simulation system is consistent with the actual location information of the network optimization client, thereby ensuring the accuracy of the simulation results and greatly improving the efficiency of network optimization.

[0123] Furthermore, the present application embodiment also proposes a visual network optimization system, such as Figure 6 As shown, the system includes a visual network optimization device and a simulation system. The visual network optimization device is used to execute the visual network optimization method in the above-mentioned visual network optimization method embodiment, which will not be described in detail here. The simulation system is set up by the visual network simulation system working method provided in the above-mentioned embodiment, and cooperates with the visual network device to complete the optimization of the network. The specific working principle and workflow are consistent with the above-mentioned embodiment, which will not be described in detail here.

[0124] Furthermore, the present application embodiment also proposes a network optimization terminal, such as Figure 7 The network optimization terminal may include: a processor (processor) 702 , a communication interface (Communications Interface) 704 , a memory (memory) 706 , and a communication bus 708 .

[0125] The processor 702, the communication interface 704, and the memory 706 communicate with each other via a communication bus 708. The communication interface 704 is used to communicate with other devices such as a client or other server network elements. The processor 702 is used to execute a program 710, which can specifically execute the relevant steps in the above-mentioned embodiment of the method for visual network optimization.

[0126] Specifically, the program 710 may include program code including computer executable instructions.

[0127] The processor 702 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiment of the present invention. The one or more processors included in the visual network terminal may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0128] The memory 706 is used to store the program 710. The memory 706 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0129] Program 710 can be specifically called by processor 702 to enable the network optimization terminal to perform the following operations:

[0130] Acquire the current location information of the network optimization client, and send the current location information to the simulation system;

[0131] Receiving simulation result information generated by the simulation system according to the current position information;

[0132] Tracking the real-time target location of the network optimization client through the simulation result information, and determining the virtual location information of the network optimization client in the simulation system according to the real-time target location information;

[0133] If the current position information is consistent with the virtual position information, the simulation result information is rendered.

[0134] Furthermore, the tracking of the real-time target position of the network optimization client through the simulation result information further includes:

[0135] The real-time target position of the network optimization client is determined according to the simulation result through three-dimensional tracking and registration technology.

[0136] Furthermore, if the current location information is inconsistent with the virtual location information, the current location information of the network optimization client is reacquired, and the current location information is sent to the simulation system to generate new simulation result information.

[0137] The simulation result information includes regional bottom layer information and regional height information;

[0138] The rendering of the simulation result information includes:

[0139] Performing data processing on the regional bottom layer information and the regional height layer information in the simulation result information;

[0140] Determine color information corresponding to the signal level value in the simulation result information;

[0141] The region bottom layer and the region height layer are three-dimensionally rendered according to the color information.

[0142] After rendering the simulation result information, the method further includes:

[0143] Determine whether there is a weak coverage area according to the rendered simulation result information;

[0144] If there is a weak coverage area, after adjusting the working parameters in the weak coverage area, the adjusted working parameters are sent to the simulation system so that the simulation system regenerates simulation result information.

[0145] After the current position information is sent to the simulation system, the method further comprises:

[0146] The simulation system searches for base stations according to the current location information, determines grid information corresponding to the coverage range of the base stations according to the searched base station information, and sends the grid information as simulation result information to the network optimization client.

[0147] The network optimization terminal provided in the above-mentioned embodiment of the present application renders the simulation results by judging whether the virtual location information of the user in the simulation system is consistent with the actual location information of the network optimization client, thereby ensuring the accuracy of the simulation results and greatly improving the efficiency of network optimization.

[0148] The algorithm or display provided herein is not inherently related to any particular computer, virtual system or other equipment. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description made to specific languages ​​above is for disclosing the best mode of the present invention.

[0149] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0150] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this method of disclosure should not be interpreted as reflecting an intention that the claimed invention requires more features than those expressly recited in each claim.

[0151] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0152] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A visual network optimization method, characterized in that: Applied to a network optimization client, the method includes: Acquire the current location information of the network optimization client, and send the current location information to the simulation system; the simulation system is set in a remote server and is a simulation model established in advance according to the network scenario information; when the simulation system receives the current location information sent by the network optimization client, it determines the corresponding scenario according to the current location information of the network optimization client, and calls different simulation models according to different scenarios; Receiving simulation result information generated by the simulation system according to the current location information, including: causing the simulation system to search for base stations according to the simulation model, and determining grid information corresponding to the coverage range of the base station according to the searched global cell identification code information and the coverage prediction calculation result, and sending the grid information as simulation result information to the network optimization client; Tracking the real-time target position of the network optimization client through the simulation result information, and determining the virtual position information of the network optimization client in the simulation system according to the real-time target position information; If the current location information is consistent with the virtual location information, the simulation result information is rendered; the real environment and simulation data are superimposed through virtual combination technology to complete the AR visualization display of the network signal.

2. The method according to claim 1, characterized in that Tracking the real-time target position of the network optimization client through the simulation result information further includes: The real-time target position of the network optimization client is determined according to the simulation result through three-dimensional tracking and registration technology.

3. The method according to claim 1, characterized in that The method further includes: if the current location information is inconsistent with the virtual location information, reacquiring the current location information of the network optimization client, and sending the current location information to the simulation system to generate new simulation result information.

4. The method according to claim 1, characterized in that The simulation result information includes regional bottom layer information and regional height information; The rendering of the simulation result information includes: Performing data processing on the regional bottom layer information and the regional height layer information in the simulation result information; Determine color information corresponding to the signal level value in the simulation result information; The region bottom layer and the region height layer are three-dimensionally rendered according to the color information.

5. The method according to claim 1, characterized in that After rendering the simulation result information, the method further includes: Determine whether there is a weak coverage area according to the rendered simulation result information; If there is a weak coverage area, after adjusting the working parameters in the weak coverage area, the adjusted working parameters are sent to the simulation system so that the simulation system regenerates simulation result information.

6. A visual network optimization device, characterized in that: include: Position information acquisition module: used to acquire current position information and send the current position information to the simulation system; The simulation system is set up in a remote server and is a simulation model established in advance according to network scenario information; when the simulation system receives the current location information sent by the network optimization client, it determines the corresponding scenario according to the current location information of the network optimization client, and calls different simulation models according to different scenarios; A simulation result information receiving module: used to receive simulation result information generated by a simulation system according to the current location information, including: enabling the simulation system to search for base stations according to the simulation model, and determining grid information corresponding to the coverage range of the base station according to the searched global cell identification code information and the coverage prediction calculation result, and sending the grid information as simulation result information to the network optimization client; Simulation result information confirmation module: used to track the real-time target position of the network optimization client through the simulation result information, and determine the virtual position information of the network optimization client in the simulation system according to the real-time target position information; confirm whether the current position information is consistent with the virtual position information; Visualization rendering module: used to render the simulation result information when the current location information is consistent with the virtual location information, and to superimpose the real environment and simulation data through virtual combination technology to complete the AR visualization display of the network signal.

7. A network optimization terminal, characterized in that: include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the visual network optimization method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The storage medium stores at least one executable instruction. When the executable instruction is executed on the network optimization terminal, the network optimization terminal executes the visual network optimization method according to any one of claims 1 to 5.

9. A visual network optimization system, characterized in that: The system includes: the visual network optimization device and simulation system as described in claim 6.

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