A control method and system for wireless network equipment

Abstract

The present application discloses a control method and system for wireless network equipment, which relates to the field of communication technology, including: collecting user data from different areas in the network; obtaining the coordinate position and transmission power parameters of the network equipment, and calculating the wireless coverage area according to the wireless signal propagation model, which includes the SCHEMA model, the Okumura model and the Hata model; determining the target area by generating a heat map according to the collected user data and the wireless coverage area; calculating the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area according to the heat map, the wireless coverage area and the user data, and the transmission power parameters; generating a control instruction to adjust the transmission power of the network equipment according to the calculated minimum transmission power value; and adjusting the transmission power of the network equipment according to the generated control instruction. In view of the problem of high energy consumption of network equipment in the prior art, the present application dynamically adjusts the transmission power of the equipment based on the user distribution, etc., thereby reducing energy consumption.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a control method and system for wireless network equipment. Background Art

[0002] For a long time, the power supply and heat dissipation of wireless network equipment has been a problem that has troubled operators. On the one hand, the coverage of traditional macro base stations is limited, and a large number of base stations need to be built to achieve full coverage. The energy consumption and maintenance costs of base stations are very high. On the other hand, with the popularization of smart terminals, users' network usage habits are becoming increasingly diversified, and network traffic distribution is showing dynamic and fragmented characteristics. The traditional fixed maximum transmission power setting method cannot adapt to the temporal and spatial distribution of network traffic, resulting in unreasonable network resource allocation and poor user experience.

[0003] In response to the above problems, academia and industry have proposed a variety of technical solutions, such as using a sleep mechanism to control the on / off of base stations, or establishing a load prediction model to dynamically adjust the transmission power. However, the sleep mechanism will reduce network availability, and it takes a long time to restart a base station after shutting down. The load prediction model requires a large amount of historical data support and is less sensitive to network changes. At present, there is no wireless network optimization solution that can respond to changes in network traffic in real time while taking into account the continuity of network coverage.

[0004] In the related technology, for example, Chinese patent document CN116669060A provides a network equipment control method, device, electronic device and storage medium, which relates to the field of communication technology and is used to reduce the energy consumption cost of base stations while ensuring basic signal coverage without affecting user access. This application includes: determining the target area according to the coverage range of each network device; the target area is located within the common coverage range of a target number of network devices; the target number is greater than or equal to a preset threshold; obtaining the number of users and resource utilization of each network device in the target area, and determining a control strategy based on the number of users and resource utilization of each network device; the control strategy is used to control the opening or closing of each network device in multiple network devices. However, this solution mainly considers the energy consumption control of the equipment, and does not take into account the network performance requirements. In complex environments, it may not be possible to achieve a balance between energy consumption control and network performance. The energy consumption of network devices in complex environments needs to be further reduced. Summary of the invention

[0005] 1. Technical issues to be solved

[0006] In response to the problem of high energy consumption of wireless network equipment in the prior art, the present application provides a control method and system for wireless network equipment. The present application dynamically adjusts the transmission power of the wireless network equipment based on user distribution, thereby reducing the energy consumption of the network equipment.

[0007] 2. Technical solution

[0008] The purpose of this application is achieved through the following technical solutions.

[0009] One aspect of an embodiment of the present specification provides a control method for a wireless network device, including: collecting user data from different areas in the network, the user data including user locations and the number of users; using the positioning technology of the base station to obtain the geographical location coordinates of each user terminal connected to the network; collecting the service traffic and access user number statistics of each base station area reported by the core network equipment; matching and associating the user location coordinate data with the service statistics data; using a grid division algorithm to grid the area at a certain interval; counting the number of user terminals in each grid unit as the user data of the grid; and calculating the ratio of the number of user terminals in each grid unit to the area of ​​the grid as the user distribution density.

[0010] Obtain the coordinate position and transmission power parameters of the network device, and calculate the wireless coverage area according to the wireless signal propagation model, wherein the wireless signal propagation model includes the SCHEMA model, the Okumura model and the Hata model; obtain the coordinate position of the network device (such as a base station, an access point, etc.). Obtain the transmission power parameters of the network device. The transmission power of network devices of different models is different, and it is necessary to obtain the wireless transmission power parameters in the technical specifications of the equipment. Calculate the wireless coverage area of ​​the network device according to the wireless signal propagation model algorithm. The wireless signal propagation models of this application include the SCHEMA model, the Okumura model, the Hata model, etc. These models take into account the path loss during signal propagation and can estimate the wireless signal strength at different distances. According to the transmission power parameters and the signal propagation model, the position of the coverage boundary can be calculated. Draw the coverage of each network device on the map, merge the overlapping areas, and you can get the overall wireless coverage area map of the network. In this application, the influence of terrain category is considered, and the above steps are repeated to calculate the network coverage under different frequency bands and different transmission power parameters.

[0011] Based on the collected user data and wireless coverage area, the target area is determined by generating a heat map; based on the heat map, wireless coverage area, user data, and transmission power parameters, the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area is calculated; the user data in the target area is obtained as the network demand parameter. The transmission power parameters of the network equipment are obtained as the network supply parameters. The power calculation model is used to calculate the minimum transmission power value that satisfies the users in the target area. The model considers the following factors: Wireless coverage model: Based on the target area and device location information, the minimum power that satisfies coverage is calculated. Wireless throughput model: Based on the number of target users and business requirements, the minimum power that satisfies throughput is calculated. Environmental factors: The impact of building obstruction and user distribution in the target area on wireless propagation.

[0012] Based on the calculated minimum transmit power value, a control instruction for adjusting the transmit power of the network device is generated; based on the calculated minimum transmit power value, a control instruction for adjusting the transmit power of the network device is generated. A control instruction is sent to the network device to adjust the transmit power to achieve dynamic power optimization for the target area. Repeat the above process to continuously optimize the network power parameters to adapt to user distribution and network changes. According to the generated control instruction, the transmit power of the network device is adjusted.

[0013] Further, the target area is generated, the grid size is set, and the wireless coverage area is divided into m*n grid units; the number of users U(i,j) in each grid unit is counted as the number of users in the corresponding grid unit; the number of users U(i,j) in each grid unit is mapped to each pixel in the corresponding grid unit to obtain the user density estimate D(i,j) of each pixel; all pixels are traversed, and a heat map of user density distribution is generated by bilinear interpolation according to the user density estimate D(i,j) of each pixel; the generated heat map is Gaussian filtered to smooth the heat map and eliminate noise; the user density threshold T is set, and the connected area with the user density estimate D(i,j) greater than T is extracted from the smoothed heat map as the target area. The specific extraction method is: take the pixel P with D(i,j)>T as the central pixel, detect the adjacent pixels in the 8 directions around P, and if the D(i,j) of the adjacent pixel is also greater than T, mark it as connected to P, repeat the above steps, and finally extract all connected areas as the target area. This application can effectively use user distribution data to generate heat maps, intelligently determine target coverage areas with dense network traffic, and provide support for subsequent transmission power optimization control.

[0014] Specifically, a heat map of user density distribution is generated by bilinear interpolation. Bilinear interpolation can obtain a continuous and smooth user density distribution based on the discrete grid user number data, avoiding the jagged edges of the heat map caused by the discretization of the number of users. The present application can generate a more refined and smooth heat map for determining the target area. The specific scheme for generating a heat map of user density distribution using bilinear interpolation is as follows: Divide the wireless coverage area into m*n grid units, each grid unit corresponding to a number of users U(i, j). Regularize the grid units into pixel grids, each pixel grid containing multiple interpolation points. For each pixel grid P(x, y), bilinear interpolation is performed according to the number of users Ui, j of the four vertices it contains to obtain the user density value D(x, y) of the pixel grid:

[0015] D(x,y)=l x × y ×U 00 +x×l y ×U 10 +l x ×y×U 01 +x×y×U 11

[0016] Here, (x, y) is the coordinate of the pixel grid, (U 00 ,U 10 ,U 01 ,U 11 ) is the number of users in the 4-vertex grid contained in the pixel grid. Repeat the above steps, traverse all pixel grids, and obtain the user density value D(x, y) of each pixel grid. According to the user density values ​​D(x, y) of all pixel grids, draw a heat map of user density distribution.

[0017] Furthermore, extracting the connected area with a user density estimate greater than a threshold as the target area includes the following steps: traversing all the pixels in the heat map, finding the pixel with a user density estimate D(x, y) greater than the threshold T as the current center pixel P. Detecting the neighboring pixels in the four directions of the center pixel P: up (x,y+1), next P down (x,y-1), left P left (x-1,y), right P right (x+1,y); detect the adjacent pixels in the four diagonal directions of the center pixel P: the upper left, upper right, lower left, and lower right leftup (x-1,y+1), upper right P righttup (x+1,y+1), bottom left P leftdown (x-1,y-1), bottom right P righdown(x+1, y-1); determine whether the user density estimate of these 8 adjacent pixels is also greater than the threshold T. If so, mark them as connected to the central pixel P. Repeat the above steps to traverse all the pixels of the heat map. By detecting the user density of adjacent pixels in the 8-neighborhood, the pixel area connected to the current central pixel can be marked to extract the target area. This application fully considers all possible connection directions and can accurately extract the target area.

[0018] Determine whether the user density estimate of the adjacent pixel points is greater than the threshold. If it is greater than the threshold, mark the corresponding adjacent pixel points as connected to the central pixel point; take the current pixel point P as the central point, and detect its 8-neighborhood adjacent pixel points Pi (i=1, 2,..., 8). Obtain the user density estimate D(Pi) for each adjacent pixel point Pi. Set the user density threshold to T. For each Pi, determine whether D(Pi) is greater than T: If D(Pi)>T, mark Pi as connected to the central pixel point P, recorded as Connected(P, Pi)=1. If D(Pi)<=T, do not mark, Connected(P, Pi)=0. Repeat the above steps until all pixels in the thermal map are scanned. Finally, the set of all adjacent pixel points marked as connected to the central pixel point P represents the area connected to P. The present application can effectively determine whether the adjacent pixel points are connected to the current central pixel point, correctly extract the target area, and provide support for subsequent transmission power control.

[0019] Repeat the above steps until all pixels in the heat map are traversed, and the connected pixels are marked as the same connected domain; traverse each pixel P in the heat map, detect the 8 neighboring pixels of P, and determine whether its user density is greater than the threshold T. If the user density of the adjacent pixel is also greater than T, mark it as connected to P and assign it the same connected domain label L. For each pixel in the same connected domain, recursively perform the search step until there is no pixel in the area whose adjacent pixel user density is greater than T. For the scanned heat map, the set of all pixels marked with the same connected domain label L constitutes a connected domain. Traverse all the obtained connected domains, and if the user density of any pixel in the connected domain is greater than T, extract the connected domain as the target area. Finally, extract all connected domains as target areas corresponding to user density greater than the threshold T. The present application can effectively mark high-density areas connected together in the heat map in a recursive manner and accurately extract these target areas.

[0020] Extract all marked connected domains as the target area corresponding to the user density greater than the threshold. Traverse all pixels and count the number of marks n of each connected domain. For each connected domain: record the coordinates (x, y) of the first marked pixel in the connected domain as the identifier of the connected domain. Query the number of marks n of the connected domain. Determine whether the number of marks n of each connected domain is greater than 0. If n>0, the user density of the pixels in the connected domain must be greater than the threshold, and all the pixel coordinates of the connected domain are added to the target area coordinate set. Traverse all connected domains, and the final target area coordinate set contains the pixel coordinates of all connected domains with a number of marks greater than 0. According to the target area coordinate set, draw the target coverage area corresponding to the user density greater than the threshold. By counting the number of marks, judging whether each connected domain should be extracted as the target area, and then drawing the area according to the coordinate set, the extraction of the connected domain of the heat map can be effectively realized, and the final target coverage area corresponding to the user density greater than the threshold can be obtained.

[0021] Furthermore, calculating the wireless coverage area includes the following steps: obtaining the coordinate position of the network device; obtaining the geographic coordinates of the macro base station, micro base station, etc. through the GPS module; obtaining the coordinates of the WiFi hotspot through positioning technology (such as triangulation positioning, etc.); obtaining the layout coordinates of small base stations, repeaters, etc. by reading the configuration information of the device.

[0022] Obtain the transmission power parameters of the network device; extract the transmission power parameters of the device from the configuration database of the network management system. Obtain the current transmission power setting of the device through the SNMP protocol. Obtain the rated parameters and adjustable range of the transmission power from the data manual of the device. Preferably, the coordinate position and transmission power parameters of the acquired network device are stored in a local database. Clean and filter the information in the database to filter out invalid or erroneous data. Generate a data record containing (device ID, coordinates, transmission power parameters) for each network device. The present application can effectively obtain the coordinates and transmission power information of network devices for use in regional coverage optimization calculations.

[0023] Determine whether the coordinate position of the network device is within the preset density area. If so, calculate the loss of the transmission power after passing through the propagation path based on the Okumura model or the Hata model; if not, calculate the loss of the transmission power after passing through the propagation path based on the SCHEMA model; represent the target area where the preset user density is greater than the threshold as area A; for each network device, obtain its coordinates (x, y); determine whether (x, y) is within area A: if (x, y) is within A, the device is within the preset density area; if (x, y) is not within A, the device is not within the preset density area. If the device is within the preset density area: calculate the transmission power propagation loss based on the Okumura model or the Hata model: If the device is not within the preset density area: calculate the transmission power propagation loss based on the SCHEMA model: Based on the calculated transmission power loss result, continue the subsequent transmission power optimization calculation. This application can select different propagation models for calculation according to the location of the network device, thereby improving the accuracy of the calculation results.

[0024] According to the calculation results of the propagation path loss, the wireless coverage area of ​​the network device is determined; in the target area where the preset user density is greater than the threshold T, the area is divided into grids of a*b meters in size. For each network device i: the transmission power of device i is obtained as Pi. The propagation distance from device i to the center of each grid is obtained as di,j. Based on the propagation model, the path loss from device i to the center of each grid unit is calculated as Li,j. The receiving power of device i is calculated as: PRi,j=PiLi,j. Determine whether the receiving power PRi,j of device i is greater than the receiving sensitivity threshold Rth: If PRi,j>Rth, it is determined that grid unit j is within the wireless coverage area of ​​device i. If PRi,j<=Rth, it is determined that grid unit j is not within the wireless coverage area of ​​device i. By traversing all network devices i, it can be finally determined whether each grid unit is within the wireless coverage area of ​​a certain device. The set of all grid units contained in the wireless coverage area of ​​any device constitutes the coverage area of ​​the entire wireless network. This application takes into account user distribution, propagation loss and receiving sensitivity threshold, and can effectively calculate the wireless coverage area of ​​each device, thereby determining the coverage area of ​​the entire wireless network and providing a basis for subsequent optimization calculations. Among them, the preset density area is the area where the number of users per square meter is greater than the threshold.

[0025] Further, based on the SCHEMA model, calculating the loss of the transmission power after passing through the propagation path includes the following steps: dividing the propagation path into n sections, and the distance on each section is di. The section divided by the propagation path refers to dividing the entire propagation path into multiple small sections in space. The basis for the division is that there are different propagation environments on the path. For example, wall loss will occur when entering indoors from outdoor, and trees will be blocked when entering the jungle from open land. These environmental change points can be used as the division positions of the sections. Dividing the entire propagation path with equal distances is also a commonly used simplified method. The path can be divided into multiple sections at a certain distance interval (such as 50 meters). Each section of the path is taken as a section, and the starting and ending distances of each section are determined to be di. For example, the first section is 0 to 50 meters, the second section is 50 meters to 100 meters, and so on. For outdoor propagation, a section can be set every 100 meters to 200 meters. The indoor propagation distance is shorter, and a section can be set every 10 meters to 20 meters. The number of divided sections n can be determined according to the path length and the complexity of the environment. The more sections there are, the higher the calculation accuracy is, but the amount of calculation is also greater. By reasonably setting the number of sections and the section distance, the propagation characteristics of each section can be calculated, the overall calculation error can be reduced, and the accuracy of the propagation loss results can be improved. On the i-th section, the distance fading Loss_distance(i) is calculated: Loss_distance(i) = 20 × log10(di), and on the i-th section, the shadow fading Loss_shadow(i) is calculated based on the section characteristics. In the SCHEMA model, shadow fading refers to the additional fading caused by obstacles on a certain section of the propagation path. For this application scenario, the calculation method of shadow fading is as follows: Analyze the environmental characteristics on each section to determine whether there are obstacles that may cause additional fading. Typical obstacles include: buildings, trees, and obstructions caused by uneven terrain. According to the empirical model or simulation fitting results, the additional fading values ​​corresponding to various obstacles are pre-set. For example, the tree attenuation is 10dB, and the light building attenuation is 15dB. When an obstacle is detected in a section, the additional fading value of the corresponding obstacle is obtained by looking up the table as the shadow fading Loss_shadow(i) on the section. If no obstacle is detected on the section, the shadow fading Loss_shadow(i) = 0. By analyzing the characteristics of each section and introducing shadow fading, the propagation loss can be calculated more accurately to determine the wireless coverage area of ​​the network equipment; on the i-th section, the combined fading is calculated:

[0026] Loss_combine(di)=Loss_distance(i)+Loss_shadow(i)

[0027] Sum the combined attenuation on each section to get the total attenuation on the propagation path:

[0028] Loss_total=∑Loss_combine(di)

[0029] i=1 to n; Loss_total is used as the final propagation path loss calculation result. The present application calculates the propagation path in sections, accurately considering the influence of distance fading and shadow fading, and can obtain a more accurate propagation loss result.

[0030] Among them, the distance fading is calculated according to the distance from each point on the cross section to the network device using the path loss index model; in this application, the propagation path loss can also be calculated based on the SCHEMA model using the following preferred scheme: introducing environmental factor correction items, adding correction items for environmental parameters such as terrain, vegetation, and buildings to the basic path loss index model, and establishing a corrected model. The model parameters are optimized using neural networks, and the model parameters are trained using a large amount of measured data using BP neural networks, etc. to obtain the optimized path loss index. Using an adaptive path loss index, the model can automatically adjust the path loss index according to the propagation distance and environmental changes to achieve self-adaptation. For example:

[0031] PL(d)=a+10n×log10(d)+f(d,h1,h2)

[0032] Among them, f(d, h1, h2) is an adaptive correction term related to distance and antenna height. According to the statistical learning method, using statistical learning methods such as Gauss process regression, the distribution of the path loss index is predicted according to the measurement data set to achieve dynamic optimization. Add global optimization constraints to increase the constraints on the overall change trend of the path loss index so that its curve is more in line with the law of propagation. This application can continuously improve the path loss index model to make it more accurate in calculating the propagation loss in complex environments.

[0033] Shadow fading uses the digital elevation model (DEM) to determine the terrain category at each point based on the terrain data of each point on the cross section, and then determines the shadow fading of each point based on the preset fading values ​​corresponding to each terrain category. Among them, terrain data refers to the original digital elevation model (DEM) data of the sampling points on the acquisition path cross section, which reflects the elevation information of the terrain. According to the DEM data, the terrain parameters such as slope, slope, and altitude can be extracted, which reflect the basic characteristics of the terrain. By comprehensively analyzing the DEM data and its derived parameters with other surface cover data (vegetation, buildings, etc.), the terrain classification can be obtained, that is, the terrain is divided into different categories, such as mountains, hills, plains, etc. The terrain category is the result of abstracting and classifying the terrain data, which reflects the overall characteristics of the terrain. Each terrain category corresponds to an empirical wireless signal fading value, which constitutes a corresponding relationship table between terrain category and fading value. According to the terrain category of the sampling point, the corresponding fading value can be found in the fading value correspondence table as the shadow fading value of the point. Therefore, terrain data is the basis for determining the terrain category, and the terrain category in turn determines the shadow fading value. The two are associated through the classification model. In summary, terrain data provides basic information, terrain categories classify and abstract it, and finally apply it to shadow fading determination.

[0034] Specifically, the following terrain classification model can be used to consider shadow fading when calculating the propagation path loss: collect digital elevation model (DEM) data of the study area and build a three-dimensional terrain database. Based on the terrain database, extract various types of terrain elements, such as buildings, vegetation, surface types, etc., to generate vector terrain layers. Use DEM-derived parameters such as terrain aspect, slope, altitude, etc., combined with the terrain layer to generate terrain classification raster data. In the terrain classification raster, each pixel is marked with a corresponding terrain type, such as mountain, hill, plain, city, etc. According to each sampling point on the propagation path, extract the terrain type of the pixel in the terrain classification raster. According to the preset terrain type and fading value correspondence table, determine the terrain shadow fading value of each sampling point. In the propagation model calculation, the terrain shadow fading value is accumulated to obtain the terrain influence. By using DEM for terrain classification, the shielding and fading effects of terrain on radio wave propagation can be effectively considered, and the accuracy of the path loss model can be improved. This terrain classification model not only takes into account the large-scale terrain, but also reflects the local environmental characteristics in detail.

[0035] Further, based on the Okumura model or the Hata model, calculating the loss of the transmission power after passing through the propagation path includes the following steps: dividing the propagation path into a number of sections; on each section, calculating the distance fading on the section, wherein the distance fading is calculated based on the distance from each point on the section to the network device and according to the path loss formula of the Okumura model or the Hata model; specifically, on the i-th section, selecting multiple representative points, and determining the distances from these points to the network device as dj. According to the Okumura model, the distance fading formula is:

[0036] Loss_distance(dj)=L0+A×log10(dj)+B

[0037] Among them, L0 is the basic loss, A and B are environmental parameters.

[0038] According to the Hata model, the distance fading formula is:

[0039] Loss_distance(dj)=a+b×log10(dj)

[0040] Where a and b are parameters. The cross section is divided into m cells. The representative distance from the jth cell to the network device is dj. For the jth cell, the path loss at the distance dj is calculated as the distance fading value Loss_distance(dj) of the cell. For the entire cross section, the distance fading values ​​of all cells are calculated and the average value is taken as the distance fading on the cross section:

[0041]

[0042] The preferred solution further encrypts the selection of representative points to more comprehensively cover the cross-sectional area. More representative points can be evenly selected. Smaller calculation units are set for important areas, and sample points at key locations are increased to accurately reflect the propagation characteristics. Weighted average fading values, points closer to network devices are given higher weights to emphasize near-zone propagation characteristics. A fading distribution diagram is established to observe the spatial distribution of fading values. Analyze the causes and optimize them in a targeted manner. Use regression technology to fit the functional relationship between distance and fading value to obtain an expression, which is substituted into any distance to calculate the fading. Add the calculation results of other models (ray tracing, finite differences, etc.) and compare and verify with the empirical model. Repeat the above steps to calculate the average distance attenuation for each section. The present application can calculate the distance attenuation on each section, and superimposing it with shadow attenuation can obtain a more accurate propagation loss. Superimpose the distance attenuation on each section to obtain the total distance attenuation on the propagation path;

[0043] According to the category of the area where the network device is located, the regional fading correction value of the Okumura model or the Hata model is obtained in the preset database; specifically, according to the coordinates of the network device, the category of the area where it is located is determined, such as dense city, suburbs, open countryside, etc. The environmental fading correction values ​​of the Okumura model and the Hata model corresponding to different regional categories are stored in the preset database. The database can be obtained through actual measurement statistics. The regional fading correction value of the Okumura model or the Hata model is determined according to the terrain category of the area where the network device is located. For the Okumura model, the following database table is set: regional category|environmental parameter A|environmental parameter B, for example: dense city|4.6|42.4; suburbs|3.6|33.5; open countryside|2.3|27.7. For the Hata model, the following database table is set: regional category|parameter a|parameter b: dense city|69.6|26.3; suburbs|46.8|33.2; open countryside|40.7|36.3. After determining the area category according to the coordinates of the network device, query the above database table to obtain the corresponding environmental fading correction value of the Okumura model or Hata model. Substituting the environmental parameters obtained from the table into the model calculation, a more accurate path loss result that takes into account regional differences can be obtained. According to the weighting method, the obtained regional fading correction value is superimposed with the total distance fading to obtain the total fading of the propagation path, and the total fading is used as the loss calculation result of the propagation path;

[0044] Further, according to the heat map, wireless coverage area and user data, and transmission power parameters, calculating the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area includes the following steps: searching the database of network devices to obtain the power adjustment interface type of the network devices, wherein the power adjustment interface type is a serial port interface and a network interface; specifically, constructing a network device database, which includes a device basic information table, an interface parameter table, and the like. The device basic information table includes information such as the device name, model, and manufacturer. The interface parameter table includes all interface ports of each device, including parameters such as the interface name, interface type (serial port / Ethernet, etc.), and transmission rate. Using an SQL query statement, the target device is located in the device basic information table with the device name / model as a keyword. The interface parameter table is associated, and all interface records of the device are retrieved using the device ID. The interface records are traversed to find interfaces of the type "serial port" or "Ethernet", which are power adjustment interfaces. The interface names and interface types of these interfaces are returned as the power adjustment interface information of the device. The interface information is stored for use when a power control instruction is subsequently sent. Repeat the above operations for all network devices to complete the retrieval of the power adjustment interface type. This application can effectively utilize the preset device database, automatically obtain the remote power control interface of the device, and prepare for subsequent transmission power optimization control work.

[0045] Read the device data manual of the network device to obtain the transmit power range supported by the network device; specifically, collect the specification sheet, user manual and other text materials of the target network device. These manuals usually contain transmit power information. Through text parsing technology, extract paragraphs containing keywords such as "transmit power" and "power range" from the manual PDF or text. Use regular expressions or text rule matching to parse the specific power values ​​and range expressions from the extracted paragraphs. Identify the parameter values ​​of the maximum transmit power Pmax and the minimum transmit power Pmin. If enumerated power levels are given, convert these discrete values ​​into continuous range representations. For example, power level 110 is converted to a 10% interval. For irregular text power range descriptions, use natural language understanding technology to extract the minimum / maximum values ​​it contains. Store the obtained transmit power value range in a database table with the device name / model as the keyword. Manually check the extraction results, correct the recognition errors, and form a device transmit power range database. Query the database according to the device model to obtain the transmit power range parameters it supports, providing a basis for optimization control. By parsing the device manual file, the transmit power range information of the device can be effectively obtained to support subsequent power optimization control.

[0046] Call the power calculation function to obtain the minimum transmit power value that meets the needs of the target area; specifically, define the power calculation function Power Calculation(), and the input parameters include: network device information device Info, location, antenna gain, frequency, etc.; target coverage area information area Info, area, user distribution, demand service and other propagation models; path loss calculation model, call the propagation model to calculate the path loss path Loss according to the device location and coverage area boundary. Calculate the required receiving sensitivity min_receive_power according to the service needs.

[0047] Min_transmit_power=min_receive_power+path_losss

[0048] If Min_transmit_power exceeds the maximum transmit power of the device, the maximum transmit power of the device is taken as the minimum transmit power. Power Calculation() returns the calculated minimum transmit power value Min_transmit_power. For each device in the network, call the Power Calculation() function and take the device information, coverage area information, and propagation model as input parameters. Get the calculated result Min_transmit_power as the minimum required transmit power of the device. Control the device to adjust the transmit power to Min_transmit_power to complete the transmit power optimization. In this way, the accurate minimum transmit power value can be obtained through the model calculation method to avoid excessive transmission of the device. Construct a power adjustment control instruction and send the instruction through the power adjustment interface to adjust the transmit power of the device.

[0049] Further, issuing instructions through the power adjustment interface to adjust the transmission power of the device includes the following steps: when the power adjustment interface type is a serial port interface, opening the serial port, setting serial port parameters, constructing a power setting instruction, and sending the instruction through the serial port; opening the corresponding serial port device file according to the previously obtained serial port parameters of the network device. Configuring serial port communication parameters, including baud rate, data bit, stop bit, parity check, etc. It needs to be consistent with the actual serial port communication parameters of the device. Constructing a serial port command for adjusting the transmission power. The command format follows the protocol specified by the device and includes fields such as start and end flags, command words, and parameters. Formatting the power value as a command parameter, inserting it into the command data packet, and completely assembling the serial port instruction for adjusting the power. Writing the constructed serial port command to the opened serial port device file. Reading the serial port feedback data to verify that the device has received the instruction. Repeating sending the serial port instruction at a certain time interval until receiving a response from the device that the execution is successful. After receiving the response, closing the serial port file to complete the adjustment process. The specific command format needs to be determined according to the communication protocol of different devices. By sending standardized control instructions to the serial port of the device, remote control of the transmission power can be flexibly achieved.

[0050] When the power adjustment interface type is a network interface, determine whether the network interface is a wireless network interface or a wired network interface; determine the interface type based on the previously obtained network device interface parameters. If the interface type is identified as Ethernet or IEEE802.3, it is determined to be a wired Ethernet interface. If the interface type is identified as IEEE802.11 or WiFi, it is determined to be a wireless WiFi interface. For other interface types, it is necessary to refer to the interface standard description to determine whether it is based on a wired connection or a wireless connection. You can also check the physical port of the interface. Most wired interfaces are RJ45 plugs, and wireless interfaces may have antennas. If you cannot judge directly, you can also try to send a test data packet to observe whether a cable connection is required. Through the above methods, you can distinguish between wired and wireless types of network interfaces. After determining the network interface type, select a suitable network protocol to assemble and send power control instructions. By comprehensively utilizing interface parameters, port characteristics, and test methods, you can effectively determine the interface type of the network device and select a suitable network communication solution for subsequent remote power control.

[0051] When it is a wireless network interface, connect to the wireless network, obtain the IP address, establish a TCP or UDP connection, and send a power setting instruction; enable the wireless network interface of the device and connect to the wireless LAN where the device is located. Obtain the IP address of the wireless network through DHCP, or manually configure a static IP address. If the device has opened the TCP / UDP service, establish a TCP or UDP connection with the device IP. You can also send a unicast UDP instruction. Construct a network command data packet to adjust the transmit power. Follow the command format specified by the application layer protocol supported by the device. Insert the calculated minimum transmit power value and other necessary parameters into the data packet. Send the network command data packet to the device through the established TCP connection or UDP channel. Parse the response packet returned by the device to confirm whether the power is set successfully. Resend the network command at a certain time interval until a successful execution response is received from the device. After the adjustment is completed, close the network connection. 10. You can also send power query commands regularly to confirm the real-time transmit power of the device.

[0052] For the wired network interface, connect the network cable, obtain the IP address, establish a TCP or UDP connection, and send the power setting instruction; use a suitable network cable to connect the wired network interface of the device and the LAN switch. Configure the IP address, subnet mask, default gateway and other parameters of the device network interface. You can set it manually or automatically obtain the IP through DHCP. Determine whether the device has opened the TCP or UDP service port. If so, establish a connection to the port through socket programming. Construct a network command data packet for adjusting the transmit power. The packet format follows the network communication protocol supported by the device. Encapsulate the transmit power value to be set in the command parameter field of the data packet. Send the network command data packet to the device through the established TCP connection or UDP channel. Parse the response data packet returned by the device to confirm whether the setting is successful. If allowed, you can continue to send query commands to obtain the real-time transmit power value of the device. After the power adjustment is completed, close the network connection and release resources. Receive the execution status and feedback value returned by the network device; parse the status field or error code in the execution status and feedback value to verify whether the power setting is successful; wherein, the execution status and feedback value are sent in the form of data packets, and the data packets are implemented by encapsulation and parsing. The data packet format is defined, including the following fields: start flag: indicates the start of a new data packet; data packet length: records the byte length of the entire data packet; data type: indicates the type of data in the data packet, such as execution status, feedback value, etc.; data content: stores the actual data to be transmitted; check code: checks the data packet content to ensure transmission accuracy; encapsulate the data packet: set the data type field according to the data type to be transmitted; encapsulate the actual data content into the data content field; calculate and fill in the data packet length field; calculate the check code and fill it into the check code field; add the packet start flag to complete the encapsulation of the entire data packet; parse the data packet: check the start flag and check code to ensure a correct data packet; parse the entire data packet according to the data packet length field; check the data type field to obtain the data category in the data packet; extract the data content field and parse the actual data; restore the data content to the execution status or feedback value according to the data type; send the encapsulated data packet through the serial port or network interface, and the receiver parses it to realize data transmission. In this way, through the encapsulation and parsing of the data packet, the transmission of structured data can be easily realized, and the flexibility and reliability of transmission can be improved.

[0053] Furthermore, when the power setting fails, resend the power setting command, or modify the parameters of the serial port interface and the network interface and reset the transmission power; analyze the failure reasons: check whether the interface connection is normal, whether the received device feedback information indicates that the execution failed, etc. If the setting fails due to problems such as the instruction format, check the serial port or network protocol, modify the instruction parameters and resend. If it is an interface connection problem, first check the physical connection of the interface, and then reconfigure the interface parameters: for the serial port interface, you can modify the baud rate, data bit, stop bit and other parameters and try again. For the network interface, you can replace the network cable, modify the IP address, subnet mask, etc. and try again. For different failure reasons, send a dedicated command to reset the interface to let the device reinitialize the interface. If the setting fails after multiple retries, you can switch to other types of interfaces (serial port / network) to try to troubleshoot the problem. Before resending all setting commands, you need to send a query command or a reset command to avoid repeated superposition of execution effects. After the setting is successful, record the valid interface parameters and instruction format to avoid the same problem. In this application, when a setting failure occurs, the success rate of retries can be improved by modifying parameters or changing interfaces.

[0054] The parameters of the serial port interface include baud rate, data bit, stop bit and parity bit; baud rate: the speed of serial communication, which indicates the number of bits transmitted per second. Common baud rates include 4800, 9600, 19200, etc. The baud rate should be consistent with the actual settings of the connected device. Data bit: the number of data bits per byte, generally 5, 6, 7 or 8 bits. The setting needs to match the device. Stop bit: the stop bit after the data bit used to mark the end of a byte. Usually set to 1 bit. Parity bit: the method for error checking. It can be set to odd parity, even parity or no parity. When configuring serial port communication, the above parameters need to be set one by one. If there is a problem with the communication, you can modify these parameters and try again: try different baud rates, generally from low to high. Modify the data bit, generally try 8 bits, if it doesn't work, try 7 or 6 bits. The stop bit remains unchanged at 1 bit, and it is only modified for special devices. Try to change the parity bit setting or turn off the parity. By adjusting these parameter combinations and comparing the communication effects under different configurations, the best parameters can be found to achieve normal communication.

[0055] The parameters of the network interface include IP address, subnet mask, default gateway and DNS server parameters. IP address: The unique identifier of the device in the network, which needs to be set to an address within the same subnet. Subnet mask: Used to divide network segments, combined with the IP address to determine whether it is in the same subnet. Default gateway: The address of the gateway device used when accessing a network that is not in this subnet. DNS server: The IP address of the domain name resolution service server. When there is a problem with network communication, you can modify the following parameters to try again: Modify the IP address and try to set another address within the same subnet. Adjust the subnet mask to expand or reduce the subnet range. Change the default gateway and use a different routing path. Configure an alternative DNS server and re-resolve the domain name. You can also try to completely reset the network interface and reconfigure the IP. Check the network cable connection status. By adjusting different combinations of network parameters and comparing the communication effects, you can find the best configuration to ensure the reliability of the network connection.

[0056] Another aspect of the embodiments of the present specification also provides a control system for a wireless network device, which executes a control method for a wireless network device of the present application, including: a user data collection module, which collects user data from different areas in the network, wherein the user data includes user locations and the number of users; a network device information acquisition module, which acquires the coordinate position and transmission power parameters of the network device; a wireless coverage area calculation module, which calculates the wireless coverage area according to a wireless signal propagation model, wherein the wireless signal propagation model includes a SCHEMA model, an Okumura model, and a Hata model; a target area determination module, which determines the target area by generating a heat map according to the collected user data and the wireless coverage area; a minimum transmission power calculation module, which calculates the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area according to the heat map, the wireless coverage area and the user data, and the transmission power parameters; a control instruction module, which generates a control instruction for adjusting the transmission power of the network device according to the calculated minimum transmission power value, and adjusts the transmission power of the network device according to the generated control instruction; a status monitoring and feedback module, which parses the device return status and verifies whether the adjustment is successful; and a model optimization module, which uses the newly added data to continuously optimize the wireless signal propagation model.

[0057] 3. Beneficial effects

[0058] Compared with the prior art, the advantages of this application are:

[0059] (1) User data analysis can determine the target coverage area and user distribution, and calculating the wireless coverage area can accurately determine the coverage requirements. The combination of the two can scientifically guide network resource allocation, control the coverage range to the minimum necessary range, avoid blindly expanding the coverage area, reduce equipment power consumption, and achieve the effect of reducing overall power consumption;

[0060] (2) The heat map reflects user distribution and network usage requirements, while user data and wireless coverage area calculation reflect user coverage requirements. The combination of the three can calculate the minimum transmission power that meets the requirements. Accurate power control instructions can control the power to this minimum value, providing only the necessary minimum power, directly reducing power consumption;

[0061] (3) The adjustment schemes of different interfaces can ensure the smooth execution of instructions. The failure retry mechanism improves the execution success rate. Accurate power control instructions can be reliably executed, so that the power of the device is controlled at the minimum necessary value, minimizing power consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0063] Figure 1 is an exemplary flow chart of a control method of a wireless network device according to some embodiments of this specification;

[0064] Figure 2 is an exemplary flow chart of calculating a wireless coverage area according to some embodiments of this specification;

[0065] Figure 3 is an exemplary flow chart for determining a target area according to some embodiments of this specification;

[0066] Figure 4 It is an exemplary module diagram of a control system of a wireless network device according to some embodiments of the present specification. DETAILED DESCRIPTION

[0067] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, without paying creative work, this specification can also be applied to other similar scenarios based on these drawings. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0068] The method and system provided in the embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0069] Figure 1 is an exemplary flow chart of a control method of a wireless network device according to some embodiments of this specification, such as Figure 1As shown, a control method for a wireless network device includes: S110 collecting user data from different areas in the network, the user data including user locations and the number of users; S120 acquiring the coordinate position and transmission power parameters of the network device, and calculating the wireless coverage area according to the wireless signal propagation model, wherein the wireless signal propagation model includes the SCHEMA model, the Okumura model and the Hata model; S130 determining the target area by generating a heat map according to the collected user data and the wireless coverage area; S140 calculating the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area according to the heat map, the wireless coverage area, the user data and the transmission power parameters; S150 generating a control instruction for adjusting the transmission power of the network device according to the calculated minimum transmission power value; S160 adjusting the transmission power of the network device according to the generated control instruction.

[0070] In a specific embodiment of the present application, area A: coordinates (100, 100), number of users 50 area B: coordinates (200, 200), number of users 30 area C: coordinates (300, 300), number of users 20 network equipment: coordinates (150, 150), maximum transmission power 20dBm1. The Okumura model is used to calculate the wireless coverage of the network device at maximum transmission power, with a radius of approximately 250 meters. The coverage is drawn on the map and overlapped with the user distribution map. It can be seen that areas A and B are within the coverage range, but area C is only partially covered. The goal is to cover all users, and a heat map is drawn with area C as the target area. Calculate the minimum receiving power (60dBm) that satisfies users in area C. The additional path loss (10dB) from the device to area C is calculated using the Okumura model. Therefore, the minimum transmission power of the device is 60dBm+10dB=50dBm. Finally, the transmission power of the network device is controlled at 50dBm, which can meet the wireless coverage of users in all target areas.

[0071] In summary, the minimum transmit power is calculated based on the user distribution and propagation model to achieve accurate power control and avoid excessive transmission. Only calculating and meeting the required power of the target coverage area can reduce unnecessary transmission and reduce energy consumption. Different models can calculate the path loss in different environments to improve the calculation accuracy. Generate a heat map to determine the target area and focus the control on covering the actual demand area. Dynamically adjust the transmit power to adapt to changes in the network environment and user distribution. Avoid blind maximum power transmission, reduce equipment circuit loss, and reduce the transmit power as much as possible while meeting coverage and capacity requirements to achieve energy saving and consumption reduction.

[0072] Figure 2 is an exemplary flow chart of calculating the wireless coverage area according to some embodiments of this specification, such as Figure 2As shown, calculating the wireless coverage area includes the following steps: S121 obtaining the coordinate position of the network device; S122 obtaining the transmission power parameters of the network device; S123 determining whether the coordinate position of the network device is located in a preset density area, S124 if yes, then based on the Okumura model or the Hata model, calculating the loss of the transmission power after passing through the propagation path; if not, then based on the SCHEMA model, calculating the loss of the transmission power after passing through the propagation path; S125 determining the wireless coverage area of ​​the network device according to the propagation path loss calculation result and the transmission power parameters of the network device; wherein the preset density area is an area where the number of users per square meter is greater than a threshold.

[0073] Among them, SCHEMA (Simplified Channel Estimation and Modeling Algorithm) is a simplified channel estimation and modeling algorithm. It extracts and processes on-site signal propagation measurement data to establish a statistical channel model, which can be used to predict the coverage range of indoor and outdoor wireless communication systems. SCHEMA model: Since it can extract statistical features from measured data and establish a channel model, it can be used to predict wireless coverage areas in complex environments, such as indoors and outdoor scenes with obstructions.

[0074] The Okumura model is an empirical model based on a large number of actual measurements, which can be used to predict the signal between the base station and the mobile station. The model takes into account the influence of parameters such as the base station antenna height, the mobile station antenna height, and the frequency. Okumura model: It can take into account the antenna height of the base station and the mobile station, and is suitable for predicting the coverage of devices at different heights in urban environments. For example, the coverage area of ​​a base station on a high-rise building, etc.

[0075] The Hata model is an extension of the Okumura model, also known as the Okumura-Hata model. It partially fits and simplifies the Okumura model to improve the convenience of calculation. The Hata model is mainly used to predict the path loss of wireless signals in urban and suburban areas. Hata model: It simplifies the Okumura model, making calculations more convenient and quickly predicting the wireless coverage in urban and suburban environments. For example, it plans the locations of various base stations covering urban areas.

[0076] The integrated application of the three models can take advantage of their respective strengths to improve the accuracy of wireless coverage area calculations in complex environments. For example, the SCHEMA model is used for indoor areas, and the Okumura and Hata models are used for urban high-rises and suburbs, so that the coverage area calculation results are more accurate. Finally, the layout of network equipment is guided according to the coverage area calculation results, so as to achieve reasonable resource allocation and reduce energy consumption. In summary, the integrated application of the three models with their advantages can improve the accuracy of wireless coverage area calculations in complex environments, thereby better guiding the deployment of network equipment and achieving energy saving.

[0077] In a specific embodiment of the present application, the coordinates (300, 400) and the transmission power 20dBm of the network device are obtained. It is determined whether the coordinates are within the preset density area, where the preset density threshold is 10 people / square meter. The user density corresponding to the query coordinate is 8 people / square meter, which is less than the threshold 10, and it is not within the preset density area. The SCHEMA model is used to calculate the path loss. The distance from the device to the user is 500 meters, and the loss is about 40dB. The actual transmission power of the device is 20dBm. According to the receiving sensitivity calculation, the coverage range of this transmission power is approximately 300 meters. It is finally determined that the wireless coverage area of ​​the network device is a circular area with (300, 400) as the center and 300 meters as the radius.

[0078] Specifically, based on the SCHEMA model, the calculation of the loss of the transmission power after passing through the propagation path includes the following steps: dividing the propagation path into several sections; on each section, calculating the distance attenuation and shadow attenuation of the section; superimposing the distance attenuation and shadow attenuation on each section to obtain the combined attenuation of each section; superimposing the combined attenuation on each section to obtain the total attenuation on the propagation path as the loss calculation result of the propagation path; wherein, the distance attenuation is calculated according to the distance from each point on the section to the network device using the path loss exponential model; the shadow attenuation is determined according to the terrain data of each point on the section using the digital elevation model DEM to determine the terrain category at each point, and then the shadow attenuation of each point is determined according to the preset attenuation values ​​corresponding to each terrain category.

[0079] In a specific embodiment of the present application, the propagation path A to B is divided into three sections S1, S2, and S3. On S1, the distance attenuation decays as the cube of the distance d; the DEM data shows that S1 is a plain, and the shadow attenuation is 0dB. The distance attenuation and shadow attenuation of each point on S1 are calculated, and then superimposed to obtain the combined attenuation. The combined attenuation of S2 and S3 is calculated in the same way. Finally, the combined attenuation of S1, S2, and S3 is added to obtain the total attenuation loss of the path A to B. Among them, if part of the area on S2 is hilly, an additional shadow attenuation value of 2dB is added to these points according to the DEM data.

[0080] Specifically, based on the Okumura model or the Hata model, calculating the loss of the transmission power after passing through the propagation path includes the following steps: dividing the propagation path into a number of sections; on each section, calculating the distance attenuation on the section, wherein the distance attenuation is calculated according to the distance from each point on the section to the network device and according to the path loss formula of the Okumura model or the Hata model; superimposing the distance attenuation on each section to obtain the total distance attenuation on the propagation path; according to the category of the area where the network device is located, obtaining the regional attenuation correction value of the Okumura model or the Hata model in a preset database; according to the weighting method, superimposing the obtained regional attenuation correction value with the total distance attenuation to obtain the total attenuation of the propagation path, and taking the total attenuation as the loss calculation result of the propagation path; wherein the regional attenuation correction value of the Okumura model or the Hata model is determined according to the terrain category of the area where the network device is located.

[0081] In a specific embodiment of the present application, the path A to B is divided into three sections S1, S2, and S3. On each section, the distance attenuation is calculated according to the formula of the Okumura model. For example, if the distance d from point P on S1 to the device is 500 meters, the distance attenuation of P is L(d)=L0+α*log(d)=55dB. The distance attenuation of each point on each section is calculated similarly. The total distance attenuation on the three sections is obtained by summing up. The area where the equipment is located is a suburb, and the regional attenuation correction value of the Okumura model is 2dB. The weighted method superimposes the distance attenuation and the regional attenuation to obtain the total attenuation of the path from A to B. The total attenuation is used as the path loss result. In this way, the present application introduces the parameters of the Okumura model such as the path index and the regional correction into the calculation to accurately calculate the propagation loss in a complex environment.

[0082] In summary, the accurate propagation loss parameters calculated can be used to determine the minimum transmit power required to cover the target area. Avoiding excessively high transmit power settings can significantly reduce the energy consumption of network equipment. Using different attenuation correction values ​​in different terrain areas can accurately match the actual needs of each area. The optimized transmit power can cover the target area while saving redundant energy consumption. Reducing base station power can reduce power consumption, cooling requirements, and operating costs. Calculating and understanding the coverage requirements of each cell in detail can help improve network energy efficiency. Lower transmit power can also reduce electromagnetic pollution to the surrounding environment. Using mature models for calculations, the results are reliable and energy waste caused by frequent adjustments can be avoided. Provide support for green wireless network planning based on big data. In summary, using the Okumura and Hata models to accurately calculate propagation loss can effectively guide network energy consumption optimization.

[0083] Specifically, according to the heat map, wireless coverage area and user data, and transmission power parameters, calculating the minimum transmission power value that meets the wireless coverage and throughput of users in the target area includes the following steps: retrieving a database of network devices to obtain the power adjustment interface type of the network device, where the power adjustment interface type is a serial port interface and a network interface; reading the device data manual of the network device to obtain the transmission power range supported by the network device; calling a power calculation function to obtain the minimum transmission power value that meets the requirements of the target area; constructing a power adjustment control instruction, issuing an instruction through the power adjustment interface, and adjusting the transmission power of the device.

[0084] In a specific embodiment of the present application, the power adjustment interface of device A retrieved from the database is a serial port. Query the device manual, A supports adjusting the transmission power range of 1723dBm. Call the calculation function, input the heat map, coverage area, business requirements, etc., and calculate that A needs to be set to 20dBm. Construct a serial port command: AT+PWR=20dBm. Open the serial port, send a serial port command, complete the power adjustment of A, and complete the power optimization. Recalculate the power regularly, update the optimization, and adapt to environmental changes. By querying the interface type and support range, the present application accurately adjusts the device power, and can flexibly issue control instructions through the serial port or network interface to achieve dynamic optimization of the wireless network.

[0085] In summary, calculations based on actual heat maps and user distribution data can accurately reflect user needs. Considering the dynamic distribution of different locations and times, the optimization results are more reliable. Calculating the minimum transmit power that meets the needs can save energy to the greatest extent. Obtaining the device support range, command control is safer and more reliable. Supporting serial ports and network interfaces, it has strong applicability. Instructions can be recalculated and issued regularly to achieve dynamic adjustment. Reducing the transmit power can reduce electricity expenses and heat consumption. Minimizing the transmit power can reduce electromagnetic pollution. Improving the refinement level of network planning is conducive to improving quality and efficiency. Dynamically calculating and adjusting the optimal transmit power of the wireless network according to actual conditions can achieve the purpose of energy saving and quality improvement.

[0086] More specifically, issuing instructions through a power adjustment interface to adjust the transmission power of a device includes the following steps: when the power adjustment interface type is a serial port interface, opening the serial port, setting serial port parameters, constructing a power setting instruction, and sending the instruction through the serial port; when the power adjustment interface type is a network interface, determining whether the network interface is a wireless network interface or a wired network interface; when it is a wireless network interface, connecting to the wireless network, obtaining an IP address, establishing a TCP or UDP connection, and sending a power setting instruction; for a wired network interface, connecting a network cable, obtaining an IP address, establishing a TCP or UDP connection, and sending a power setting instruction; receiving an execution status and feedback value returned by a network device; parsing the status field or error code in the execution status and feedback value to verify whether the power setting is successful; wherein the execution status and feedback value are sent in the form of data packets, and the data packets are implemented by encapsulation and parsing.

[0087] In a specific embodiment of the present application, it is determined that the power adjustment interface of device B is an Ethernet wired network interface. Connect the network cable and obtain the IP address 192.168.1.105. Establish a TCP connection with port number 4000. Construct a command data packet: [Command type: 1][Power value: 22][Device ID: B]; send the command data packet through TCP Socket. Device B returns a data packet: [Status: Success][Power value: 22dBm][Device ID: B]. Parse the data packet, obtain the execution status as successful, and verify that the setting is successful. If the parsed status is an error, retry or alarm. Repeat the above process to control the transmission power of other devices. By encapsulating the command data packet and sending it, parsing the feedback packet to verify the execution effect, the network interface can be used flexibly and reliably to remotely control the transmission power of wireless devices.

[0088] More specifically, when the power setting fails, the power setting instruction is resent, or the transmission power is reset after modifying the parameters of the serial port interface and the network interface; the parameters of the serial port interface include baud rate, data bit, stop bit and check bit; the parameters of the network interface include IP address, subnet mask, default gateway and DNS server parameters.

[0089] In a specific embodiment of the present application, the power of device C is set, and the return status is failure. The interface of C is a serial port, and the original parameters are baud rate 9600, data bit 8, stop bit 1, and no parity. Modify the serial port parameters to baud rate 115200, data bit 8, stop bit 1, odd parity. Reconstruct the serial port instruction and send the power setting instruction. The parsing return result is successful, and the setting is complete. If the setting still fails, further modify the parameters: change the data bit to 7, the stop bit to 2, and the even parity. Repeat the instruction until it succeeds. For the network interface, you can modify the IP address, subnet mask, and gateway to reset it. If the setting is successful after modifying the IP and gateway, the new parameters are recorded. By modifying the serial port parameters or resetting the network parameters, the fault tolerance of the power control can be improved.

[0090] Figure 3 is an exemplary flow chart for determining a target area according to some embodiments of this specification, such as Figure 3 As shown, according to the collected user data and wireless coverage area, determining the target area by generating a heat map includes the following steps: S131 sets the grid size to divide the wireless coverage area into a number of grid units; S132 calculates the number of users in each grid unit as the number of users in the corresponding grid unit; S133 maps the number of users in each grid unit to each pixel in the corresponding grid unit as the user density estimation of each pixel; S134 traverses all pixels and generates a heat map of user density distribution according to the user density estimation of each pixel; S135 uses Gaussian filtering to smooth the generated heat map; S136 extracts the connected area with a user density estimation greater than a threshold value from the smoothed heat map as the target area.

[0091] In a specific embodiment of the present application, the grid size is set to 50 meters × 50 meters, and the coverage area is divided into 10 × 10 grids. Count the number of users in each grid: A (8), B (12), C (7), D (3), E (10)...; map the number of users to 100 × 100 pixels in the grid, and in the grid with 8 users, the user density of each pixel is set to 0.08. Traverse all pixels of the grid and draw a heat map of the user density distribution. Use a Gaussian filter (radius 5 pixels) to smooth the heat map. Set the density threshold to 0.06, and extract the connected areas A, B, E, and F with user density exceeding 0.06 as the target area. After the target area is determined, calculate the minimum transmission power that meets the user coverage and capacity requirements in the area; adjust the transmission power of the network equipment according to the calculation results.

[0092] In summary, the use of grid division and pixel mapping can intuitively reflect the user distribution and avoid errors in calculations. The heat map is clear and intuitive, and uses color depth to reflect user density, which is easy to analyze. Gaussian filtering can eliminate noise or abnormal points in the heat map. Setting a density threshold extracts key areas to facilitate identification of priority areas for network planning. Pixel-level connected domains extract target areas, avoiding the inaccuracy caused by polygonal representation.

[0093] Specifically, extracting a connected area with a user density estimate greater than a threshold as a target area includes the following steps: taking a pixel with a user density estimate greater than a threshold as a central pixel, detecting adjacent pixels in eight directions of the central pixel, namely, up, down, left, right, upper left, upper right, lower left, and lower right; judging whether the user density estimate of the adjacent pixels is greater than a threshold, and if so, marking the corresponding adjacent pixels as connected to the central pixel; repeating the above steps until all pixels in the heat map are traversed, marking the connected pixels as the same connected domain; extracting all marked connected domains as the target area corresponding to a user density greater than the threshold.

[0094] In a specific embodiment of the present application, all pixels in the heat map are traversed to find pixel A with a user density > 0.06 as the center pixel. Detect the adjacent pixels B, C, D, E, F, G, H, and I in eight directions: above, below, left, right, upper left, upper right, lower left, and lower right of A. Determine whether the user density of B~I is > 0.06, and those that are greater are marked as connected to A. With the newly added connected pixel as the center pixel, repeat the above steps and detect eight directions until the traversal is complete. Mark the connected pixels as the same connected domain. Repeat until all pixels have been traversed. Extract all marked connected domains as the target area. In this way, through eight-direction detection and marking, all connected areas in the heat map with a user density greater than the threshold can be completely extracted as the target coverage area for network optimization to avoid gaps.

[0095] In summary, in this way, the present application intuitively uses the heat map to extract areas with high user density as target areas for network optimization, thereby achieving flexible and efficient wireless network power control. The adjacent relationship of pixels in eight directions is fully considered, which avoids the gaps that may appear when there are only four directions, and improves the integrity of the extracted connected areas. By marking the connected domain in a recursive manner, connected target areas of any shape can be correctly extracted. Directly acting at the pixel level, errors or inaccuracies in graphic polygon processing are avoided. The threshold of user density can be flexibly set to extract target areas with different demand levels. The algorithm flow is simple and clear, the amount of calculation is small, and the target area can be extracted quickly.

[0096] Figure 4is an exemplary module diagram of a control system of a wireless network device according to some embodiments of this specification, such as Figure 4 As shown, a control system 200 of a wireless network device executes a control method of a wireless network device of the present application, including: a user data collection module 210, collecting user data of different areas in the network, the user data including user location and user quantity; a network device information acquisition module 220, acquiring the coordinate position and transmission power parameter of the network device; a wireless coverage area calculation module 230, calculating the wireless coverage area according to the wireless signal propagation model, the wireless signal propagation model including the SCHEMA model, the Okumura model and the Hata model; a target area determination module 240, determining the target area by generating a heat map according to the collected user data and the wireless coverage area; a minimum transmission power calculation module 250, calculating the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area according to the heat map, the wireless coverage area and the user data, and the transmission power parameter; a control instruction module 260, generating a control instruction for adjusting the transmission power of the network device according to the calculated minimum transmission power value, and adjusting the transmission power of the network device according to the generated control instruction; a state monitoring and feedback module 270, parsing the device return state to verify whether the adjustment is successful; and a model optimization module 280, continuously optimizing the wireless signal propagation model using the newly added data.

[0097] In summary, the user data collection module collects the location and number of users in different areas to obtain the network load distribution. The network device information acquisition module obtains the coordinate position and transmission power parameters of the device. The wireless coverage area calculation module calculates the coverage area based on the wireless signal propagation model, and the model can be continuously optimized. The target area determination module generates a heat map based on the user distribution to determine the target coverage area. The minimum transmission power calculation module combines the heat map, coverage area, user data, etc. to calculate the minimum transmission power that meets the coverage and throughput of the target area. According to the calculation results, a control instruction is generated to adjust the transmission power of the network device. The monitoring feedback module verifies whether the adjustment is successful. In this way, by collecting user distribution and network device information, intelligently calculating and adjusting the transmission power, the transmission power of the network device can be reduced while ensuring the quality of wireless coverage in the target area, thereby achieving the purpose of energy saving and consumption reduction. This application is dynamically adjusted in combination with user distribution, and network energy consumption can be continuously optimized.

Claims

1. A method for controlling a wireless network device, comprising: Collect user data from different areas of the network, including user location and number of users; Obtain the coordinate position and transmission power parameters of the network device, and calculate the wireless coverage area according to the wireless signal propagation model, where the wireless signal propagation model includes SCHEMA model, Okumura model and Hata model; Based on the collected user data and wireless coverage area, the target area is determined by generating a heat map; Calculate the minimum transmit power value that meets the wireless coverage and throughput of users in the target area based on the heat map, wireless coverage area and user data, and transmit power parameters; Generate a control instruction for adjusting the transmission power of the network device according to the calculated minimum transmission power value; According to the generated control instructions, the transmission power of the network equipment is adjusted; Among them, SCHEMA model is Simplified Channel Estimation and Modeling Algorithm; The loss of the transmission power after passing through the propagation path based on the SCHEMA model includes: Divide the propagation path into several sections; On each cross section, the distance attenuation and shadow attenuation of the cross section are calculated; The distance fading and shadow fading on each section are superimposed to obtain the combined fading of each section; The combined attenuation on each cross section is superimposed to obtain the total attenuation on the propagation path, which is used as the loss calculation result of the propagation path; Among them, distance fading is calculated using the path loss exponential model based on the distance from each point on the cross section to the network device; Shadow fading is based on the terrain data of each point on the cross section. The digital elevation model (DEM) is used to determine the terrain category at each point, and then the shadow fading of each point is determined according to the preset fading values ​​corresponding to each terrain category.

2. The control method of the wireless network device according to claim 1, characterized in that: Based on the collected user data and wireless coverage area, determining the target area by generating a heat map includes the following steps: Set the grid size to divide the wireless coverage area into several grid units; Calculate the number of users in each grid unit as the number of users in the corresponding grid unit; Map the number of users in each grid unit to each pixel in the corresponding grid unit as the user density estimation of each pixel; Traverse all pixels and generate a heat map of user density distribution based on the user density estimation of each pixel; Use Gaussian filtering to smooth the generated heat map; For the smoothed heat map, the connected areas where the user density estimate is greater than the threshold are extracted as the target areas.

3. The control method of the wireless network device according to claim 2, characterized in that: Extracting the connected area where the user density estimate is greater than the threshold as the target area includes the following steps: Taking the pixel whose user density estimation is greater than the threshold as the central pixel, detect the adjacent pixels in eight directions: up, down, left, right, upper left, upper right, lower left, and lower right of the central pixel; Determine whether the user density estimate of the adjacent pixel points is greater than a threshold. If so, mark the corresponding adjacent pixel points as being connected to the central pixel point. Repeat the above steps until all pixels in the heat map are traversed, and the connected pixels are marked as the same connected domain; The connected areas of all tags are extracted as the target areas corresponding to the user density greater than the threshold.

4. The control method of the wireless network device according to claim 1, characterized in that: Calculating the wireless coverage area includes the following steps: Get the coordinates of the network device; Obtain the transmit power parameters of network devices; Determine whether the coordinate position of the network device is within the preset density area. If so, calculate the loss of the transmission power after passing through the propagation path based on the Okumura model or the Hata model. If not, then based on the SCHEMA model, calculate the loss of the transmitted power after passing through the propagation path; Determine the wireless coverage area of ​​the network device based on the propagation path loss calculation result and the transmission power parameter of the network device; The preset density area is an area where the number of users per square meter is greater than a threshold.

5. The control method of the wireless network device according to claim 4, characterized in that: Based on the Okumura model or the Hata model, the calculation of the transmission power loss after passing through the propagation path includes the following steps: Divide the propagation path into several sections; On each cross section, the distance attenuation on the cross section is calculated, where the distance attenuation is calculated based on the distance from each point on the cross section to the network device and the path loss formula of the Okumura model or the Hata model; The distance attenuation on each cross section is superimposed to obtain the total distance attenuation on the propagation path; According to the category of the area where the network device is located, the regional fading correction value of the Okumura model or the Hata model is obtained from the preset database; According to the weight method, the obtained regional fading correction value is superimposed with the total distance fading to obtain the total fading of the propagation path, and the total fading is used as the loss calculation result of the propagation path; The regional fading correction value of the Okumura model or the Hata model is determined according to the terrain type of the area where the network equipment is located.

6. The control method of the wireless network device according to claim 4, characterized in that: According to the heat map, wireless coverage area and user data, and transmit power parameters, calculating the minimum transmit power value that satisfies the wireless coverage and throughput of users in the target area includes the following steps: Retrieve a database of network devices to obtain a power adjustment interface type of the network device, wherein the power adjustment interface type is a serial port interface and a network interface; Read the device data sheet of the network device to obtain the transmit power range supported by the network device; call the power calculation function to obtain the minimum transmit power value that meets the requirements of the target area; construct a power adjustment control instruction, issue the instruction through the power adjustment interface, and adjust the transmit power of the device.

7. The control method of the wireless network device according to claim 6, characterized in that: The following steps are used to issue commands through the power adjustment interface to adjust the transmit power of the device: When the power adjustment interface type is a serial port interface, open the serial port, set the serial port parameters, construct a power setting instruction, and send the instruction through the serial port; When the power adjustment interface type is a network interface, determining whether the network interface is a wireless network interface or a wired network interface; When it is a wireless network interface, connect to the wireless network, obtain the IP address, establish a TCP or UDP connection, and send a power setting instruction; For the wired network interface, connect the network cable, obtain the IP address, establish a TCP or UDP connection, and send a power setting command; Receive the execution status and feedback value returned by the network device; parse the status field or error code in the execution status and feedback value to verify whether the power setting is successful; The execution status and feedback value are sent in the form of data packets, which are implemented by encapsulation and parsing.

8. The control method of the wireless network device according to claim 7, characterized in that: When the power setting fails, resend the power setting command, or modify the parameters of the serial port interface and the network interface and then reset the transmission power; The parameters of the serial port interface include baud rate, data bit, stop bit and check bit; The parameters of the network interface include IP address, subnet mask, default gateway and DNS server parameters.

9. A system based on the control method of the wireless network device according to any one of claims 1 to 8, comprising: A user data collection module, which collects user data in different areas of the network, wherein the user data includes user locations and the number of users; A network device information acquisition module is used to obtain the coordinate position and transmission power parameters of the network device; A wireless coverage area calculation module calculates the wireless coverage area according to a wireless signal propagation model, wherein the wireless signal propagation model includes a SCHEMA model, an Okumura model, and a Hata model; The target area determination module determines the target area by generating a heat map based on the collected user data and the wireless coverage area; The minimum transmit power calculation module calculates the minimum transmit power value that satisfies the wireless coverage and throughput of users in the target area based on the heat map, wireless coverage area and user data, and transmit power parameters; A control instruction module generates a control instruction for adjusting the transmit power of the network device according to the calculated minimum transmit power value, and adjusts the transmit power of the network device according to the generated control instruction; Status monitoring and feedback module, which analyzes the status returned by the equipment and verifies whether the adjustment is successful; Model optimization module, which uses the newly added data to continuously optimize the wireless signal propagation model.

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