Antenna radiation direction determination method, device, equipment, medium and program product

Abstract

The present application discloses a method, device, equipment, medium and program product for determining antenna radiation direction, belonging to the field of wireless communication technology, the method comprising: obtaining measurement channel data of a base station; modeling a statistical channel model according to an antenna pattern and a first propagation mechanism to obtain first predicted channel data; preliminarily optimizing the statistical channel model according to the measurement channel data, the first predicted channel data and a first optimization algorithm, and obtaining a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model; modeling the preliminarily optimized statistical channel model according to the preliminary antenna radiation direction and a second propagation mechanism to obtain second predicted channel data; re-optimizing the preliminarily optimized statistical channel model according to the measurement channel data, the second predicted channel data and a second optimization algorithm, and obtaining the target antenna radiation direction according to the re-optimized statistical channel model. The accurate antenna radiation direction can be obtained.

Description

Technical Field

[0001] The present application belongs to the field of wireless communication technology, and in particular, relates to a method, device, equipment, medium and program product for determining an antenna radiation direction. Background Art

[0002] Base station antennas have the advantages of long transmission distance and strong anti-destruction capability, and are an important means of communication. Accurately measuring the radiation direction of the antenna is very important for using the antenna for communication.

[0003] For the measurement of antenna radiation direction, in the relevant technology, tower workers can obtain the antenna radiation direction by directly observing the radiation of the base station antenna and filling in the relevant data. This method has the problem of insufficient accuracy. Moreover, due to the lack of a clear coordinate system, tower workers are prone to positioning errors during the observation process, resulting in the inability to fully and accurately reflect the actual situation of the base station antenna radiation. Drone tower measurement is another method for measuring the antenna radiation direction. The specific method is that the drone performs multi-layer 360-degree measurements around the base station tower to draw a radiation heat map or signal heat map to determine the antenna radiation direction. Although this method has improved the coverage and efficiency of detection to a certain extent, it still faces many challenges. On the one hand, the flight time of drones is limited, making it difficult to achieve long-term continuous detection. On the other hand, some areas may prohibit flight, making it impossible for drones to operate freely in all areas. These restrictions make drone detection subject to many constraints in practical applications, and it is difficult to meet the needs of long-term and wide-range base station antenna radiation direction detection.

[0004] Therefore, there is an urgent need for a method that can accurately measure the radiation direction of an antenna. Summary of the invention

[0005] The embodiments of the present application provide a method, apparatus, device, medium and program product for determining the radiation direction of an antenna, which can obtain an accurate antenna radiation direction and improve measurement efficiency to meet the needs of long-term and wide-range base station antenna radiation direction detection.

[0006] In a first aspect, the present application provides a method for determining an antenna radiation direction, the method comprising:

[0007] Obtaining measurement channel data of a base station;

[0008] Modeling a statistical channel model according to the antenna pattern and the first propagation mechanism to obtain first predicted channel data;

[0009] Preliminarily optimizing the statistical channel model according to the measured channel data, the first predicted channel data, and the first optimization algorithm, and obtaining a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model;

[0010] The statistical channel model after preliminary optimization is modeled according to the preliminary antenna radiation direction and the second propagation mechanism to obtain second predicted channel data, and the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism;

[0011] The statistical channel model after the preliminary optimization is optimized again according to the measured channel data, the second predicted channel data and the second optimization algorithm, and the target antenna radiation direction is obtained according to the statistical channel model after the optimization again.

[0012] In some embodiments of the present application, the statistical channel model is preliminarily optimized according to the measured channel data, the first predicted channel data, and the first optimization algorithm, and a preliminary antenna radiation direction is obtained according to the preliminarily optimized statistical channel model, including:

[0013] Repeat the following steps until the model convergence condition is met to obtain a preliminary optimized statistical channel model. The antenna radiation direction corresponding to the model convergence is used as the preliminary antenna radiation direction:

[0014] Calculating a value of a first loss function according to the measured channel data, the first predicted channel data, and the first optimization algorithm;

[0015] Determine a first model adjustment parameter according to a value of the first loss function;

[0016] Adjusting the model parameters of the statistical channel model according to the first model adjustment parameter to obtain the channel model after the first parameter adjustment;

[0017] Prediction is performed according to the channel model adjusted with the first parameter to obtain first predicted channel data.

[0018] In some embodiments of the present application, the statistical channel model after preliminary optimization is optimized again according to the measured channel data, the second predicted channel data and the second optimization algorithm, and the target antenna radiation direction is obtained according to the statistical channel model after the optimization, including:

[0019] Repeat the following steps until the model convergence condition is met to obtain the statistical channel model after optimization again. The antenna radiation direction corresponding to the model convergence is used as the target antenna radiation direction:

[0020] Calculating a value of a second loss function according to the measured channel data, the second predicted channel data, and the second optimization algorithm;

[0021] Determine a second model adjustment parameter according to a value of a second loss function;

[0022] Adjusting the model parameters of the statistical channel model after preliminary optimization according to the second model adjustment parameters to obtain the channel model after the second parameter adjustment;

[0023] Prediction is performed according to the channel model adjusted by the second parameter to obtain second predicted channel data.

[0024] In some embodiments of the present application, the first optimization algorithm and the second optimization algorithm are any one of a bird colony algorithm, an ant colony algorithm, a particle swarm algorithm, an annealing algorithm, and an artificial intelligence algorithm.

[0025] In some embodiments of the present application, after re-optimizing the statistical channel model after the preliminary optimization according to the measured channel data, the second predicted channel data and the second optimization algorithm, and obtaining the target antenna radiation direction according to the re-optimized statistical channel model, the method further includes:

[0026] Through simulation with the statistical channel model optimized again, a preset number of location points with the largest spatial differences in the monitoring area of ​​the base station are determined;

[0027] Constructing an expected monitoring matrix based on the field strength information of a preset number of location points;

[0028] Comparing the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, wherein the actual monitoring matrix is ​​a monitoring matrix established based on field strength information obtained by periodically performing actual measurements on the monitored locations;

[0029] Determine the difference between the actual direction and the expected direction of the antenna radiation based on the comparison result;

[0030] The monitoring strategy for adjusting the antenna radiation direction is based on the differences.

[0031] In some embodiments of the present application, a preset number of location points with the largest spatial differences in the monitoring area of ​​the base station are determined by simulating the statistical channel model after optimization again, including:

[0032] The antenna radiation direction in the statistical channel model after multiple adjustments and optimization is obtained to obtain the channel information of multiple position points output by the model after each adjustment, wherein the channel information includes field strength information;

[0033] The field strength information of multiple locations is counted to determine the location points with the largest spatial sum change of the field strength at a preset number of locations in the monitoring area.

[0034] In some embodiments of the present application, before comparing the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, the method further includes:

[0035] Monitoring anchor points are set up at a preset number of location points, and actual field strength information of the location points monitored by the monitoring anchor points is periodically measured to obtain actual field strength information of the preset number of location points;

[0036] An actual monitoring matrix is ​​established based on actual field strength information of a preset number of location points.

[0037] In a second aspect, an embodiment of the present application provides a device for determining an antenna radiation direction, the device comprising:

[0038] An acquisition module, used to acquire measurement channel data of a base station;

[0039] A first modeling module, used to model a statistical channel model according to the antenna pattern and the first propagation mechanism to obtain first predicted channel data;

[0040] A first optimization module, used to preliminarily optimize the statistical channel model according to the measured channel data, the first predicted channel data and the first optimization algorithm, and obtain a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model;

[0041] A second modeling module is used to model the statistical channel model after preliminary optimization according to the preliminary antenna radiation direction and the second propagation mechanism to obtain second predicted channel data, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism;

[0042] The second optimization module is used to re-optimize the statistical channel model after the preliminary optimization according to the measured channel data, the second predicted channel data and the second optimization algorithm, and obtain the target antenna radiation direction according to the re-optimized statistical channel model.

[0043] In a third aspect, an embodiment of the present application provides a device for determining an antenna radiation direction, the device comprising: a processor and a memory storing computer program instructions;

[0044] When the processor executes the computer program instructions, the method for determining the antenna radiation direction of any of the above embodiments is implemented.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method for determining the antenna radiation direction of any of the above embodiments is implemented.

[0046] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining the antenna radiation direction of any of the above embodiments.

[0047] According to the method, apparatus, equipment, medium and program product for determining the antenna radiation direction provided by the implementation of the present application, the radiation direction of the antenna is first roughly adjusted according to the actually measured channel data of the base station and the first propagation mechanism, and the antenna radiation pattern to obtain a preliminary antenna radiation direction, and then the radiation direction of the antenna is fine-tuned based on the actually measured channel data of the base station, the preliminary antenna radiation direction and the second propagation mechanism, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism. Therefore, the accurate antenna radiation direction can be finally obtained, and the measurement efficiency can be improved to meet the long-term and wide-range base station antenna radiation direction detection needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0049] Figure 1 A schematic diagram of a flow chart of a method for determining an antenna radiation direction provided in an embodiment of the present application;

[0050] Figure 2 Another schematic diagram of a flow chart of a method for determining an antenna radiation direction provided in an embodiment of the present application;

[0051] Figure 3 A schematic diagram of a structure of a device for determining the antenna radiation direction provided in an embodiment of the present application;

[0052] Figure 4 Another structural schematic diagram of a device for determining antenna radiation direction provided in an embodiment of the present application;

[0053] Figure 5 A schematic diagram of the structure of a device for determining the antenna radiation direction provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0056] Base station antennas have the advantages of long transmission distance and strong anti-destruction capability, and are an important means of communication. Accurately measuring the radiation direction of the antenna is very important for using the antenna for communication.

[0057] For the measurement of antenna radiation direction, in the relevant technology, tower workers can obtain the antenna radiation direction by directly observing the radiation of the base station antenna and filling in the relevant data. This method has the problem of insufficient accuracy. Moreover, due to the lack of a clear coordinate system, tower workers are prone to positioning errors during the observation process, resulting in the inability to fully and accurately reflect the actual situation of the base station antenna radiation. Drone tower measurement is another method for measuring the antenna radiation direction. The specific method is that the drone performs multi-layer 360-degree measurements around the base station tower to draw a radiation heat map or signal heat map to determine the antenna radiation direction. Although this method has improved the coverage and efficiency of detection to a certain extent, it still faces many challenges. On the one hand, the flight time of drones is limited, making it difficult to achieve long-term continuous detection. On the other hand, some areas may prohibit flight, making it impossible for drones to operate freely in all areas. These restrictions make drone detection subject to many constraints in practical applications, and it is difficult to meet the needs of long-term and wide-range base station antenna radiation direction detection.

[0058] In order to solve the above technical problems, the embodiments of the present application provide a method, device, equipment, medium and program product for determining the radiation direction of an antenna, which can obtain accurate antenna radiation direction and improve measurement efficiency to meet the long-term and wide-range base station antenna radiation direction detection needs.

[0059] Figure 1 A schematic diagram of a flow chart of a method for determining an antenna radiation direction provided in an embodiment of the present application;

[0060] Next, combine Figure 1 A method for determining the antenna radiation direction according to an embodiment of the present application is introduced, and the method comprises the following steps:

[0061] S110, obtaining measurement channel data of a base station;

[0062] S120, modeling a statistical channel model according to the antenna pattern and the first propagation mechanism to obtain first predicted channel data;

[0063] S130, preliminarily optimizing the statistical channel model according to the measured channel data, the first predicted channel data, and the first optimization algorithm, and obtaining a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model;

[0064] S140, modeling the statistical channel model after preliminary optimization according to the preliminary antenna radiation direction and the second propagation mechanism to obtain second predicted channel data, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism;

[0065] S150, re-optimizing the initially optimized statistical channel model according to the measured channel data, the second predicted channel data and the second optimization algorithm, and obtaining the target antenna radiation direction according to the re-optimized statistical channel model.

[0066] According to the method for determining the antenna radiation direction provided by the implementation of the present application, the radiation direction of the antenna is first roughly adjusted according to the actually measured channel data of the base station and the first propagation mechanism and the antenna radiation pattern to obtain a preliminary antenna radiation direction, and then the radiation direction of the antenna is fine-tuned based on the actually measured channel data of the base station, the preliminary antenna radiation direction and the second propagation mechanism, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism. Therefore, the accurate antenna radiation direction can be finally obtained, and the measurement efficiency can be improved to meet the long-term and wide-range base station antenna radiation direction detection needs.

[0067] For the above S110, multiple receiving terminals may be set up at multiple locations around the base station to obtain initial channel measurement data, or the channel data may be obtained directly through drive testing. These receiving terminals obtain measurement channel data by receiving signals transmitted from the base station. The measurement channel data generally includes signal strength (RSSI), path loss, delay, fading characteristics, etc.

[0068] For the above S120, the antenna pattern shows the distribution of the antenna's radiation intensity in different directions. Using this diagram, you can get a preliminary understanding of the antenna's radiation pattern and main radiation direction.

[0069] The first propagation mechanism can simulate the propagation behavior of the signal in the environment, help predict the propagation and intensity attenuation of the signal at different spatial positions, and combine with the real-scene channel measurement data to help calibrate and adjust the antenna radiation model. The first propagation mechanism includes but is not limited to direct radiation, transmission, diffraction, etc. Specifically, for example, direct radiation, single transmission, single diffraction, etc. The first propagation mechanism is a simple propagation mechanism, which is used to preliminarily estimate the signal propagation path and lock the approximate radiation direction of the antenna. It is suitable for the coarse adjustment stage, with small amount of calculation and fast convergence speed.

[0070] Combined with the statistical channel model, the actual measured channel data (such as received signal strength RSSI, path loss, etc.) is used to correct the prediction results of the propagation mechanism. The statistical channel model can capture the characteristics of fading and interference in signal propagation, and adjust the model parameters to make it closer to the actual situation.

[0071] For the above S130, the first optimization algorithm is an approximation optimization algorithm, which can be any one of a bird colony algorithm, an ant colony algorithm, a particle swarm algorithm, an annealing algorithm, and an artificial intelligence algorithm. By continuously adjusting the model parameters, the value of the loss function is minimized, thereby approximating the actual signal propagation characteristics. This step is a rough adjustment stage, which quickly converges to a general direction through a simplified propagation model to ensure the basis for subsequent fine tuning.

[0072] In some embodiments of the present application, the statistical channel model is preliminarily optimized according to the measured channel data, the first predicted channel data, and the first optimization algorithm, and a preliminary antenna radiation direction is obtained according to the preliminarily optimized statistical channel model, including:

[0073] Repeat the following steps until the model convergence condition is met to obtain a preliminary optimized statistical channel model. The antenna radiation direction corresponding to the model convergence is used as the preliminary antenna radiation direction:

[0074] Calculating a value of a first loss function according to the measured channel data, the first predicted channel data, and the first optimization algorithm;

[0075] Determine a first model adjustment parameter according to a value of the first loss function;

[0076] Adjusting the model parameters of the statistical channel model according to the first model adjustment parameter to obtain the channel model after the first parameter adjustment;

[0077] Prediction is performed according to the channel model adjusted with the first parameter to obtain first predicted channel data.

[0078] Specifically, the first loss function can be the following formula:

[0079] =

[0080] in, is the measurement channel data, is the first predicted channel data predicted based on the statistical channel model. The channel data may be field strength. is the measurement location point. The above objective function is a reference. The actual indicators considered include but are not limited to the estimation result error, trend change consistency (such as Pearson correlation coefficient), etc.

[0081] After calculating the value of the first loss function, the gradient of the statistical channel model can be calculated according to the value of the first loss function, and the model parameters of the statistical channel model can be adjusted according to the calculated gradient to obtain the channel model after the first parameter adjustment, and prediction can be continued according to the adjusted model until the model converges. The condition for the model convergence may be that the value of the first loss function is less than a preset value or the number of model iterations reaches a maximum number of iterations.

[0082] For the above S140, the second propagation mechanism is a complex propagation mechanism. The signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism, and can more accurately reflect the complexity of the actual environment. The second propagation mechanism includes but is not limited to direct radiation, transmission, reflection, directional scattering, diffraction, etc. Specifically, it can be multiple reflections, multiple diffractions, etc.

[0083] After rough adjustment, the approximate radiation direction of the antenna has been determined. According to the approximate radiation direction of the antenna and more complex propagation mechanisms, the statistical channel model after preliminary optimization can be more complexly modeled to obtain second predicted channel data that is more in line with the actual environment.

[0084] For the above S150, the second optimization algorithm is an approximation optimization algorithm, which can be any one of a bird colony algorithm, an ant colony algorithm, a particle swarm algorithm, an annealing algorithm, and an artificial intelligence algorithm. By continuously adjusting the model parameters, the value of the loss function is minimized, thereby approximating the actual signal propagation characteristics. This step is a fine-tuning stage, and the accurate radiation direction of the antenna is converged through a complex propagation model.

[0085] In some embodiments of the present application, the statistical channel model after preliminary optimization is optimized again according to the measured channel data, the second predicted channel data and the second optimization algorithm, and the target antenna radiation direction is obtained according to the statistical channel model after the optimization, including:

[0086] Repeat the following steps until the model convergence condition is met to obtain the statistical channel model after optimization again. The antenna radiation direction corresponding to the model convergence is used as the target antenna radiation direction:

[0087] Calculating a value of a second loss function according to the measured channel data, the second predicted channel data, and the second optimization algorithm;

[0088] Determine a second model adjustment parameter according to a value of a second loss function;

[0089] Adjusting the model parameters of the statistical channel model after preliminary optimization according to the second model adjustment parameters to obtain the channel model after the second parameter adjustment;

[0090] Prediction is performed according to the channel model adjusted by the second parameter to obtain second predicted channel data.

[0091] The model adjustment process used in the fine-tuning stage can be consistent with that in the coarse-tuning stage and will not be described in detail here.

[0092] Through the embodiments of the present application, different granularity detections of the antenna radiation direction are performed based on a combination of multiple propagation mechanisms, which effectively improves the accuracy and efficiency of the antenna radiation direction detection and provides a reliable basis for subsequent monitoring.

[0093] Figure 2 Another schematic diagram of a flow chart of a method for determining an antenna radiation direction provided in an embodiment of the present application;

[0094] In some embodiments of the present application, after the statistical channel model after the preliminary optimization is optimized again according to the measured channel data, the second predicted channel data and the second optimization algorithm, and the target antenna radiation direction is obtained according to the statistical channel model after the optimization, the method for determining the antenna radiation direction further includes the following steps:

[0095] S210, performing simulation by the statistical channel model optimized again to determine a preset number of location points with the largest spatial differences in the monitoring area of ​​the base station;

[0096] S220, constructing an expected monitoring matrix according to field strength information of a preset number of location points;

[0097] S230, comparing the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, wherein the actual monitoring matrix is ​​a monitoring matrix established based on field strength information obtained by periodically performing actual measurements on monitored locations;

[0098] S240, determining a difference between an actual direction and an expected direction of antenna radiation according to the comparison result;

[0099] S250, adjusting a monitoring strategy of the antenna radiation direction according to the difference.

[0100] Regarding S210, the statistical channel model after further optimization can output field strength information of multiple location points, and the field strength information of these location points can be counted. A preset number of location points with the largest spatial differences can be found in the monitoring area of ​​the base station.

[0101] Specifically, in some embodiments of the present application, a preset number of location points with the largest spatial differences in the monitoring area of ​​the base station are determined by simulation using the statistical channel model after optimization again, including:

[0102] The antenna radiation direction in the statistical channel model after multiple adjustments and optimization is obtained to obtain the channel information of multiple position points output by the model after each adjustment, wherein the channel information includes field strength information;

[0103] The field strength information of multiple locations is counted to determine the location points with the largest spatial sum change of the field strength at a preset number of locations in the monitoring area.

[0104] The field strength space refers to the distribution of wireless signal strength in a specific area. It reflects the three-dimensional spatial distribution of how the signal strength changes at different spatial locations, and is usually used to analyze and optimize the coverage effect and channel quality of wireless communication systems.

[0105] After adjusting the radiation direction of the antenna in the system, the location points with the largest spatial sum of field strength changes represent that these location points are most sensitive to the antenna radiation direction and are sensitive location points. After obtaining the sensitive location points, these sensitive location points can be monitored to facilitate the monitoring of the antenna radiation direction.

[0106] For example, after adjusting the angle of the antenna in the system, by measuring the field strength changes at 100 points, the 20 points with the largest changes can be found. These points reflect the significant changes in the signal propagation characteristics after the antenna adjustment. These 20 points will be monitored intensively to ensure effective tracking of sensitive changes in the antenna radiation direction.

[0107] Regarding S220, the field strength information of a preset number of location points is aggregated to obtain an expected monitoring matrix reflecting the dynamic changes of the field strength.

[0108] S230, the actual monitoring matrix is ​​a monitoring matrix established based on the field strength information obtained by periodically measuring the monitored location points, and the actual monitoring matrix reflects the actual dynamic changes of the field strength. The actual monitoring matrix is ​​compared with the expected monitoring matrix to determine the difference between the two, that is, the comparison result.

[0109] In some embodiments of the present application, before comparing the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, the method further includes:

[0110] Monitoring anchor points are set up at a preset number of location points, and actual field strength information of the location points monitored by the monitoring anchor points is periodically measured to obtain actual field strength information of the preset number of location points;

[0111] An actual monitoring matrix is ​​established based on actual field strength information of a preset number of location points.

[0112] The anchor point can collect the field strength data of antenna radiation in real time to ensure the accuracy and reliability of monitoring. By periodically measuring the actual field strength data at the same point, an actual monitoring matrix can be constructed to facilitate the comparison of the actual monitoring matrix with the expected monitoring matrix to monitor the antenna radiation direction.

[0113] Regarding S240, the actual monitoring matrix and the expected monitoring matrix may be subtracted to obtain a comparison result, and the comparison result between the two may be used as the difference between the two.

[0114] Regarding S250, a preset threshold can be set, for example, 5dB. When the difference between the actual monitoring matrix and the expected monitoring matrix does not exceed 5dB, the monitoring strategy of the antenna radiation direction is not adjusted. When the difference between the actual monitoring matrix and the expected monitoring matrix exceeds 5dB, the monitoring strategy of the antenna radiation direction is adjusted. The preset threshold can also be other values, which can be determined according to actual conditions.

[0115] The difference between the actual monitoring matrix and the expected monitoring matrix may be due to the construction of new buildings around the base station, which blocks the signal, or the change of the antenna's azimuth angle. When it is determined that there are new buildings around the base station, the monitoring points can be adjusted. When it is determined that the antenna's azimuth angle has changed, the antenna's azimuth angle can be adjusted.

[0116] Through the embodiments of the present application, the actual monitoring matrix is ​​compared with the expected matrix constructed by the theoretical model. Through comparative analysis, the difference between the actual and expected conditions of antenna radiation can be observed, thereby realizing normalized antenna radiation monitoring. Not only can the direction and intensity of antenna radiation be monitored in real time, but also the monitoring strategy can be quickly responded and adjusted during the antenna adjustment process to ensure the continuity and effectiveness of monitoring. Efficient and accurate monitoring of antenna radiation conditions is achieved, and the accuracy and stability of monitoring are improved.

[0117] Figure 3 A schematic diagram of a structure of a device for determining the antenna radiation direction provided in an embodiment of the present application;

[0118] Next, combine Figure 3 An apparatus for determining an antenna radiation direction provided in an embodiment of the present application is introduced, and the apparatus includes:

[0119] An acquisition module 301 is used to acquire measurement channel data of a base station;

[0120] A first modeling module 302, configured to model a statistical channel model according to an antenna pattern and a first propagation mechanism to obtain first predicted channel data;

[0121] A first optimization module 303 is used to preliminarily optimize the statistical channel model according to the measured channel data, the first predicted channel data and the first optimization algorithm, and obtain a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model;

[0122] The second modeling module 304 is used to model the statistical channel model after preliminary optimization according to the preliminary antenna radiation direction and the second propagation mechanism to obtain second predicted channel data, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism;

[0123] The second optimization module 305 is used to re-optimize the statistical channel model after the preliminary optimization according to the measured channel data, the second predicted channel data and the second optimization algorithm, and obtain the target antenna radiation direction according to the re-optimized statistical channel model.

[0124] In some embodiments of the present application, the first optimization module 303 is specifically used to:

[0125] Repeat the following steps until the model convergence condition is met to obtain a preliminary optimized statistical channel model. The antenna radiation direction corresponding to the model convergence is used as the preliminary antenna radiation direction:

[0126] Calculating a value of a first loss function according to the measured channel data, the first predicted channel data, and the first optimization algorithm;

[0127] Determine a first model adjustment parameter according to a value of the first loss function;

[0128] Adjusting the model parameters of the statistical channel model according to the first model adjustment parameter to obtain the channel model after the first parameter adjustment;

[0129] Prediction is performed according to the channel model adjusted with the first parameter to obtain first predicted channel data.

[0130] In some embodiments of the present application, the second optimization module 305 is specifically used to:

[0131] Repeat the following steps until the model convergence condition is met to obtain the statistical channel model after optimization again. The antenna radiation direction corresponding to the model convergence is used as the target antenna radiation direction:

[0132] Calculating a value of a second loss function according to the measured channel data, the second predicted channel data, and the second optimization algorithm;

[0133] Determine a second model adjustment parameter according to a value of a second loss function;

[0134] Adjusting the model parameters of the statistical channel model after preliminary optimization according to the second model adjustment parameters to obtain the channel model after the second parameter adjustment;

[0135] Prediction is performed according to the channel model adjusted by the second parameter to obtain second predicted channel data.

[0136] In some embodiments of the present application, the first optimization algorithm and the second optimization algorithm are any one of a bird colony algorithm, an ant colony algorithm, a particle swarm algorithm, an annealing algorithm, and an artificial intelligence algorithm.

[0137] The embodiment of the present application improves the accuracy and efficiency of antenna radiation monitoring by repeatedly calling the matching of ray tracing simulation results and actual measurement results.

[0138] Figure 4 Another structural schematic diagram of a device for determining antenna radiation direction provided in an embodiment of the present application;

[0139] Combination Figure 4 In some embodiments of the present application, the device for determining the antenna radiation direction further includes:

[0140] The first determination module 401 is used to re-optimize the statistical channel model after the preliminary optimization according to the measured channel data, the second predicted channel data and the second optimization algorithm, and after obtaining the target antenna radiation direction according to the re-optimized statistical channel model, determine a preset number of position points with the largest spatial differentiation in the monitoring area of ​​the base station through simulation of the re-optimized statistical channel model;

[0141] A first construction module 402 is used to construct an expected monitoring matrix according to field strength information of a preset number of location points;

[0142] The comparison module 403 is used to compare the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, wherein the actual monitoring matrix is ​​a monitoring matrix established based on the field strength information obtained by periodically measuring the field strength information of the monitored location points;

[0143] A second determination module 404, configured to determine the difference between the actual direction and the expected direction of antenna radiation according to the comparison result;

[0144] The adjustment module 405 is used to adjust the monitoring strategy of the antenna radiation direction according to the difference.

[0145] In some embodiments of the present application, the first determination module 401 is specifically used to:

[0146] The antenna radiation direction in the statistical channel model after multiple adjustments and optimization is obtained to obtain the channel information of multiple position points output by the model after each adjustment, wherein the channel information includes field strength information;

[0147] The field strength information of multiple locations is counted to determine the location points with the largest spatial sum change of the field strength at a preset number of locations in the monitoring area.

[0148] In some embodiments of the present application, the device for determining the antenna radiation direction further includes:

[0149] The measurement module is used to set up monitoring anchor points at a preset number of location points before comparing the actual monitoring matrix with the expected monitoring matrix and obtaining the comparison result, and periodically measure the actual field strength information of the location points monitored by the monitoring anchor points to obtain the actual field strength information of the preset number of location points;

[0150] The second building module is used to establish an actual monitoring matrix according to actual field strength information of a preset number of location points.

[0151] According to the device for determining the antenna radiation direction provided by the implementation of the present application, the radiation direction of the antenna is first roughly adjusted according to the actually measured channel data of the base station and the first propagation mechanism and the antenna radiation pattern to obtain a preliminary antenna radiation direction, and then the radiation direction of the antenna is finely adjusted based on the actually measured channel data of the base station, the preliminary antenna radiation direction and the second propagation mechanism, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism. Therefore, the accurate antenna radiation direction can be finally obtained, and the measurement efficiency can be improved to meet the long-term and wide-range base station antenna radiation direction detection needs.

[0152] Figure 5 A schematic diagram of the structure of a device for determining the antenna radiation direction provided in an embodiment of the present application;

[0153] The device for determining the antenna radiation direction may include a processor 501 and a memory 502 storing computer program instructions.

[0154] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0155] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 502 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0156] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0157] The processor 501 implements the method for determining the antenna radiation direction in the above embodiment by reading and executing the computer program instructions stored in the memory 502 .

[0158] In one example, the device for determining the antenna radiation direction may further include a communication interface 503 and a bus 510. Figure 5 As shown, the processor 501, the memory 502, and the communication interface 503 are connected via a bus 510 and communicate with each other.

[0159] The communication interface 503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0160] Bus 510 includes hardware, software or both, and couples the components of the antenna radiation direction determination device to each other. For example, but not limitation, the bus may include an accelerated graphics port (AGP) or other graphics bus, an enhanced industry standard architecture (EISA) bus, a front-side bus (FSB), a hypertransport (HT) interconnect, an industry standard architecture (ISA) bus, an infinite bandwidth interconnect, a low pin count (LPC) bus, a memory bus, a microchannel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 510 may include one or more buses. Although the present application embodiment describes and illustrates a specific bus, the present application considers any suitable bus or interconnect.

[0161] The antenna radiation direction determination device executes the antenna radiation direction determination method in the embodiment of the present application, thereby achieving Figure 1 , Figure 2 A method for determining the radiation direction of an antenna.

[0162] In addition, in combination with the method for determining the antenna radiation direction in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the methods for determining the antenna radiation direction in the above embodiment is implemented.

[0163] In combination with the method for determining the antenna radiation direction in the above embodiments, an embodiment of the present application also provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining the antenna radiation direction of any of the above embodiments.

[0164] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0165] The functional blocks shown in the structural block diagram described above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier. "Machine-readable medium" may include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0166] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0167] Aspects of the present disclosure are described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0168] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for determining an antenna radiation direction, characterized in that: The method comprises: Obtaining measurement channel data of a base station; Modeling a statistical channel model according to the antenna pattern and a first propagation mechanism to obtain first predicted channel data, wherein the first propagation mechanism is used to simulate the propagation behavior of the signal in the environment, to help predict the propagation of the signal at different spatial positions and the intensity attenuation, and to help calibrate and adjust the antenna radiation model, and the first propagation mechanism includes direct radiation, transmission and diffraction; Preliminarily optimizing the statistical channel model according to the measured channel data, the first predicted channel data and a first optimization algorithm, and obtaining a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model; Modeling the preliminary optimized statistical channel model according to the preliminary antenna radiation direction and the second propagation mechanism to obtain second predicted channel data, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism, wherein the second propagation mechanism includes direct radiation, transmission, reflection, directional scattering and diffraction; The statistical channel model after the preliminary optimization is optimized again according to the measured channel data, the second predicted channel data and the second optimization algorithm, and the target antenna radiation direction is obtained according to the statistical channel model after the optimization again.

2. The method according to claim 1, characterized in that The preliminarily optimizing the statistical channel model according to the measured channel data, the first predicted channel data and the first optimization algorithm, and obtaining a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model, comprises: Repeat the following steps until the model convergence condition is reached to obtain a preliminary optimized statistical channel model, and use the antenna radiation direction corresponding to the model convergence as the preliminary antenna radiation direction: Calculating a value of a first loss function according to the measured channel data, the first predicted channel data, and a first optimization algorithm; Determine a first model adjustment parameter according to the value of the first loss function; Adjusting the model parameters of the statistical channel model according to the first model adjustment parameters to obtain a channel model after the first parameters are adjusted; Prediction is performed based on the channel model adjusted with the first parameters to obtain first predicted channel data.

3. The method according to claim 1, characterized in that The step of re-optimizing the preliminarily optimized statistical channel model according to the measured channel data, the second predicted channel data, and the second optimization algorithm, and obtaining the target antenna radiation direction according to the re-optimized statistical channel model includes: Repeat the following steps until the model convergence condition is reached to obtain a statistical channel model that has been optimized again, and use the antenna radiation direction corresponding to the model convergence as the target antenna radiation direction: Calculating a value of a second loss function according to the measured channel data, the second predicted channel data, and a second optimization algorithm; Determine a second model adjustment parameter according to the value of the second loss function; Adjusting the model parameters of the preliminarily optimized statistical channel model according to the second model adjustment parameters to obtain a channel model after the second parameter adjustment; Prediction is performed according to the channel model adjusted by the second parameter to obtain second predicted channel data.

4. The method according to claim 1, characterized in that: The first optimization algorithm and the second optimization algorithm are any one of a bird colony algorithm, an ant colony algorithm, a particle swarm algorithm, an annealing algorithm and an artificial intelligence algorithm.

5. The method according to any one of claims 1 to 4, characterized in that: After re-optimizing the preliminarily optimized statistical channel model according to the measured channel data, the second predicted channel data and the second optimization algorithm, and obtaining the target antenna radiation direction according to the re-optimized statistical channel model, the method further includes: By performing simulation with the re-optimized statistical channel model, a preset number of location points with the largest spatial differences in the monitoring area of ​​the base station are determined; Constructing an expected monitoring matrix according to the field strength information of the preset number of location points; Comparing the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, wherein the actual monitoring matrix is ​​a monitoring matrix established based on field strength information obtained by periodically performing actual measurements on monitored locations; Determine the difference between the actual direction and the expected direction of the antenna radiation according to the comparison result; A monitoring strategy for the antenna radiation direction is adjusted according to the difference.

6. The method according to claim 5, characterized in that The simulating by the re-optimized statistical channel model to determine a preset number of location points with the largest spatial differences in the monitoring area of ​​the base station includes: Adjusting the antenna radiation direction in the re-optimized statistical channel model multiple times to obtain channel information of multiple position points output by the model after each adjustment, wherein the channel information includes field strength information; The field strength information of the plurality of location points is counted to determine a preset number of location points in the monitoring area where the spatial sum of the field strength has the largest change.

7. The method according to claim 5, characterized in that Before comparing the actual monitoring matrix with the expected monitoring matrix to obtain a comparison result, the method further includes: Setting up monitoring anchor points at the preset number of location points, periodically measuring actual field strength information of the location points monitored by the monitoring anchor points, and obtaining actual field strength information of the preset number of location points; An actual monitoring matrix is ​​established according to the actual field strength information of the preset number of location points.

8. A device for determining antenna radiation direction, characterized in that: The device comprises: An acquisition module, used to acquire measurement channel data of a base station; A first modeling module is used to model a statistical channel model according to an antenna pattern and a first propagation mechanism to obtain first predicted channel data, wherein the first propagation mechanism is used to simulate the propagation behavior of a signal in an environment, to help predict the propagation of a signal at different spatial positions and the intensity attenuation, and to help calibrate and adjust an antenna radiation model, wherein the first propagation mechanism includes direct radiation, transmission, and diffraction; A first optimization module, configured to preliminarily optimize the statistical channel model according to the measured channel data, the first predicted channel data, and a first optimization algorithm, and obtain a preliminary antenna radiation direction according to the preliminarily optimized statistical channel model; A second modeling module is used to model the preliminary optimized statistical channel model according to the preliminary antenna radiation direction and a second propagation mechanism to obtain second predicted channel data, wherein the signal propagation characteristics of the second propagation mechanism are closer to the actual environment where the base station is located than the signal propagation characteristics of the first propagation mechanism, wherein the second propagation mechanism includes direct radiation, transmission, reflection, directional scattering and diffraction; The second optimization module is used to re-optimize the statistical channel model after the preliminary optimization according to the measured channel data, the second predicted channel data and the second optimization algorithm, and obtain the target antenna radiation direction according to the re-optimized statistical channel model.

9. A device for determining antenna radiation direction, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for determining the antenna radiation direction according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining the antenna radiation direction according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining the antenna radiation direction as described in any one of claims 1 to 7.

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