CN116347495A

CN116347495A - Method, device, equipment and storage medium for measuring and calculating antenna azimuth angle

Info

Publication number: CN116347495A
Application number: CN202111598822.0A
Authority: CN
Inventors: 徐佳芸; 肖炜; 林睿; 蒋华; 乔艳
Original assignee: China Telecom International Co ltd
Current assignee: China Telecom International Co ltd
Priority date: 2021-12-24
Filing date: 2021-12-24
Publication date: 2023-06-27

Abstract

The disclosure provides a method, a device, equipment and a storage medium for measuring and calculating an antenna azimuth angle, and relates to the technical field of communication. The method comprises the following steps: acquiring industrial parameter data of a base station antenna and measurement report MR data of a terminal, wherein the MR data comprises Reference Signal Received Power (RSRP); and determining the azimuth angle of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal by combining the relation between the RSRP and the antenna distance and angle.

Description

Method, device, equipment and storage medium for measuring and calculating antenna azimuth angle

Technical Field

The disclosure relates to the field of communication technologies, and in particular, to a method, a device, equipment and a storage medium for measuring and calculating an antenna azimuth angle.

Background

Currently, mobile internet technology is rapidly developed, and higher requirements are put forward for wireless network optimization. The wireless network optimization work needs accurate and real wireless network data, particularly basic data of engineering parameters, and if the engineering parameters are inaccurate, great negative effects are brought to the network optimization work.

Antenna azimuth is an important engineering parameter. Currently, antenna azimuth is typically measured manually by a worker at the time of installation. However, there is an error between the azimuth angle and the actual angle due to the influence of manpower, measuring instruments, construction environments, and the like.

It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

The present disclosure provides a method, apparatus, device and storage medium for measuring and calculating an azimuth angle of an antenna, which solve, at least to some extent, the problem of an error between an azimuth angle and an actual angle in the related art.

Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.

According to one aspect of the present disclosure, there is provided a method of measuring an azimuth angle of an antenna, the method comprising:

acquiring industrial parameter data of a base station antenna and measurement report MR data of a terminal, wherein the MR data comprises Reference Signal Received Power (RSRP);

and determining the azimuth angle of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal by combining the relation between the RSRP and the antenna distance and angle.

In one embodiment of the present disclosure, determining an azimuth angle of a base station antenna based on parameter data of the base station antenna and measurement report MR data of a terminal in combination with a relationship between RSRP and an antenna distance and angle includes:

Determining a coverage sector of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal by combining the relation between RSRP and the antenna distance and angle;

based on the coverage sector of the base station antenna, the azimuth angle of the base station antenna is determined in combination with the MR data in the sector.

In one embodiment of the present disclosure, the process data includes sector location and sector transmit power, and the MR data further includes terminal location; based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal, combining the relation between RSRP and the antenna distance and angle, the coverage sector of the base station antenna is determined, which comprises the following steps:

based on the terminal position, carrying out aggregation processing on the MR data to obtain a distribution diagram of the MR data;

based on the MR data distribution diagram, combining the relation between the sector position, the sector transmitting power and the RSRP and the antenna distance and angle, the coverage sector of the base station antenna is determined.

In one embodiment of the present disclosure, the industrial parameter data further includes a base station ID and a sector ID, and the MR data further includes a base station ID and a sector ID; based on the distribution diagram of the MR data, combining the relation between the sector position, the sector transmitting power and the RSRP and the antenna distance and angle, before determining the coverage sector of the base station antenna, the method further comprises:

Based on the base station ID and the sector ID, the industrial parameter data and MR data are associated.

In one embodiment of the present disclosure, the aggregation processing of MR data based on the terminal position includes:

and based on the terminal position, a DBSCAN algorithm is applied to aggregate the MR data.

In one embodiment of the present disclosure, determining an azimuth angle of a base station antenna based on a coverage sector of the base station antenna in combination with MR data within the sector, comprises:

rasterizing an image corresponding to a coverage sector of a base station antenna to obtain a plurality of grids;

dividing a plurality of grids into a plurality of distance intervals according to the distance between each grid and a base station;

according to MR data contained in each grid, calculating to obtain the weight of each grid;

determining a reference point in grids contained in the distance interval according to the weight of each grid;

an azimuth angle of the base station antenna is determined based on the location of the reference point and the location of the base station.

In one embodiment of the present disclosure, determining an azimuth angle of a base station antenna based on a location of a reference point and a location of a base station includes:

respectively calculating azimuth angles between the base station and a plurality of reference points to obtain a plurality of first azimuth angles;

an azimuth angle of the base station antenna is determined based on the plurality of first azimuth angles.

In one embodiment of the present disclosure, the method further comprises:

and calibrating the azimuth angle of the antenna in the industrial parameter data based on the azimuth angle of the antenna of the base station.

According to another aspect of the present disclosure, there is provided an apparatus for measuring an azimuth angle of an antenna, the apparatus comprising:

the data acquisition module is used for acquiring the industrial parameter data of the base station antenna and the measurement report MR data of the terminal, wherein the MR data comprises Reference Signal Received Power (RSRP);

the azimuth measuring and calculating module is used for determining the azimuth of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal and combining the relation between RSRP and the antenna distance and angle.

According to still another aspect of the present disclosure, there is provided an electronic apparatus including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described method of estimating antenna azimuth via execution of the executable instructions.

According to yet another aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described method of estimating antenna azimuth angle.

The method for measuring and calculating the azimuth angle of the antenna provided by the embodiment of the disclosure can determine the azimuth angle of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal and combining the relation between RSRP and the distance and angle of the antenna. The antenna azimuth angle obtained in this way is more accurate, and can be used for correcting the antenna azimuth angle in engineering parameters.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.

FIG. 1 is a schematic flow chart of a method for measuring and calculating an azimuth angle of an antenna according to an embodiment of the disclosure;

FIG. 2 is a second flow chart of a method for measuring an azimuth angle of an antenna according to the embodiment of the disclosure;

FIG. 3 is a diagram of a geographic distribution of MR data in an embodiment of the disclosure;

FIG. 4 is a schematic diagram of the MR data rasterization principles in an embodiment of the present disclosure;

FIG. 5 is a schematic diagram of the principle of azimuth angle measurement in the embodiment of the present disclosure;

fig. 6 is a schematic diagram of a distance distribution of a sector coverage grid from a base station in an embodiment of the disclosure;

FIG. 7 is a schematic diagram of a range bin azimuth calculation reference point distribution in an embodiment of the disclosure;

FIG. 8 is a diagram of an azimuth angle measurement result in an embodiment of the present disclosure;

FIG. 9 is a schematic diagram of an apparatus for measuring and calculating an azimuth angle of an antenna according to an embodiment of the disclosure; and

fig. 10 is a block diagram of a computer device in an embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.

Based on the background, there is a problem that there is an error between the azimuth angle and the actual angle in the related art.

Antenna azimuth is an important engineering parameter, and if the engineering parameter is inaccurate, the network optimization work is greatly negatively affected.

The number of base stations in the current mobile network is large, the basic data volume to be maintained is large, a large amount of manpower and material resources are often required to be spent for testing and calibrating to acquire the actual engineering parameters of the current network, and the efficiency and the accuracy are low. The basic data acquisition, checking and calibration work is always one of the high-cost and low-yield works in the wireless network optimization.

In view of the above problems, the method for measuring and calculating the azimuth angle of the antenna provided by the embodiment of the present disclosure may determine the azimuth angle of the base station antenna based on the parameter data of the base station antenna and the measurement report MR data of the terminal, in combination with the relationship between RSRP and the antenna distance and angle. The azimuth angle of the antenna obtained in this way is more accurate, and after the engineering parameters are corrected by using the azimuth angle, the engineering parameters can be used for optimizing the network.

For ease of understanding, the following first describes terms and related techniques involved in the present disclosure.

MR (Measurement Report ) MR is one of the main grounds for evaluating the quality of a wireless environment. For the GSM system, MR is a main means for obtaining wireless information of a terminal at a network side, and mainly includes uplink signal information and downlink signal information.

The downlink signal information is measured and collected by a network terminal and reported to the network through MR signaling of a Um port; the uplink signal information is measured and collected by BTS at the network side, and the BTS gathers the uplink and downlink measurement information and reports the information to BSC through MR. The uplink and downlink signal information may specifically include RSRP (Reference Signal Receiving Power, reference signal received power), reference signal received quality, time advance, eNodeB antenna arrival angle, eNodeB received interference power, and the like.

RSRP is one of the key parameters that can represent the radio signal strength and the physical layer measurement requirements in an LTE network, and is the average value of the signal power received on all REs (resource elements) that carry reference signals within a certain symbol.

The base station generally comprises a BBU (Building Baseband Unite, indoor baseband processing unit), an RRU (Remote Radio Unite, remote radio frequency module) and an antenna feed system.

The BBU is generally arranged in a machine room in a centralized way, and the RRU is generally mounted by holding a pole or hanging a wall. The RRU mainly completes the modulation and demodulation of the radio frequency signals, the power amplification of the radio frequency analog signals and the transmission to the antenna feed system.

The antenna feed system comprises an antenna and a feeder, wherein the antenna is connected with the RRU through the feeder. The antenna can be installed on the iron tower, and a plurality of antennas can be installed on the iron tower of a base station.

It should be noted that, according to the base station, the corresponding installation mode of the antenna in the embodiment of the present disclosure may be different, and is not limited to being installed in the iron tower.

The base stations may include various forms of macro base stations, micro base stations, relay stations, access points, and the like. In systems employing different radio access technologies, the names of base station capable devices may vary, for example in LTE systems, called enodebs or enbs; in a 5G NR-U system, it is called gNodeB or gNB.

In some scenarios, a "base station" may also be referred to as a "cell". As communication technology evolves, the description of "base station" may change.

There are many types of antennas. For example, by wavelength, medium wave antennas, short wave antennas, ultra-short wave antennas, microwave antennas, etc. may be included; according to performance, the antenna can comprise a high gain antenna, a medium gain antenna and the like; the directional antenna can comprise an omni-directional antenna, a sector antenna and the like; according to the purposes, the antenna can comprise a base station antenna, a television antenna, a radar antenna, a radio station antenna and the like; the antenna can comprise a line antenna, a surface antenna and the like according to the structure; depending on the type of system, it may include unit antennas, antenna arrays, etc.

The antenna in the embodiments of the present disclosure may be a directional antenna or a sector antenna as described above.

As one example, the antenna in embodiments of the present disclosure may be a plate-shaped directional antenna. The plate-shaped directional antenna may comprise a radiating element, a reflecting plate, a power distribution network.

Here, the radiating element may be a vibrator, the reflecting plate may be a bottom plate, and the power distribution network may be a feeding network.

In addition, the antenna may also include packaging protection, such as radomes.

When radio waves propagate in space, the electric field direction changes according to a certain rule, and this phenomenon is called polarization of the radio waves.

Dual polarization, i.e. 2 antenna elements in one unit, forms two independent waves. By adopting the dual-polarized antenna, the number of antennas can be reduced when a cell is covered, the requirement on the conditions of antenna erection is reduced, the investment is further reduced, and the coverage effect can be ensured.

Among the characteristics of the antenna, a very important capability is the radiation distance. The radiating distance of the antenna can be further increased by adding the vibrator.

In cities, the crowds are dense, and buildings stand up, and directional antennas are usually required to cover a specified range. And a reflecting plate blocked at one side. Then, a plurality of vibrators are combined, and "focusing" can be performed.

The antenna body is typically mounted at a high elevation with a downward inclination, and the azimuth to be measured in the embodiments of the present disclosure is the azimuth when the antenna is mounted.

The method for measuring and calculating the antenna azimuth angle provided by the embodiment of the disclosure can be executed by any electronic equipment with calculation processing capability. For example, the execution body of the network traffic feature extraction method may be, but not limited to, any terminal device, server, or the execution body of the method that can be configured to execute the method for measuring and calculating the antenna azimuth provided by the embodiments of the present disclosure, or may be a client itself that can execute the method.

The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs (Content Delivery Network, content delivery networks), basic cloud computing services such as big data and artificial intelligent platforms, and the like.

The terminal may be a variety of electronic devices including, but not limited to, smartphones, tablets, laptop portable computers, desktop computers, wearable devices, augmented reality devices, virtual reality devices, etc., which are not limited herein.

The present exemplary embodiment will be described in detail below with reference to the accompanying drawings and examples.

Fig. 1 shows a flowchart of a method for measuring and calculating an azimuth angle of an antenna in an embodiment of the disclosure, as shown in fig. 1, the method for measuring and calculating an azimuth angle of an antenna provided in the embodiment of the disclosure includes the following steps:

step S102, acquiring industrial parameter data of a base station antenna and measurement report MR data of a terminal, wherein the MR data comprises reference signal received power RSRP;

step S104, based on the parameter data of the base station antenna and the measurement report MR data of the terminal, combining the relation between RSRP and the antenna distance and angle, determining the azimuth angle of the base station antenna.

The following describes the above steps in detail, as follows:

in some embodiments, determining the azimuth angle of the base station antenna based on the parameter data of the base station antenna and the measurement report MR data of the terminal in combination with the RSRP versus antenna distance and angle may include:

In some embodiments, the parametric data may include sector locations and sector transmit powers, and the MR data may also include terminal locations.

Accordingly, determining the coverage sector of the base station antenna based on the parameter data of the base station antenna and the measurement report MR data of the terminal in combination with the relation between RSRP and the antenna distance and angle may include:

The "position" in the above embodiment may specifically be latitude and longitude information.

In some embodiments, the tool data may also include a base station ID and a sector ID, and the MR data may also include a base station ID and a sector ID.

Before determining the coverage sector of the base station antenna based on the profile of MR data in combination with the relationship of sector location, sector transmit power, and RSRP to antenna distance and angle, the method may further comprise:

As an example, as shown in fig. 2, the industrial parameter data may include a base station ID, a sector ID, a latitude and longitude of a sector, and a sector transmission power; AGPS MR data may include base station ID, sector ID, RSRP signal strength, and location data (longitude and latitude) of signals received by a plurality of handset terminals in each sector.

Fig. 3 shows the geographical distribution of AGPS MR data, i.e. the MR data obtained by aggregating the MR data based on the terminal position as described above. In this profile, each gray dot corresponds to 1 or more pieces of MR data.

As an example, where MR data is aggregated, a DBSCAN algorithm may be applied.

In the azimuth calculation process, a machine learning algorithm is required to cluster grids, and a DBSCAN algorithm is adopted here: the core idea of the DBSCAN is to start from a certain core point and continuously expand towards a region with reachable density, so that a maximized region comprising the core point and the boundary point is obtained, and any two points in the region are connected with each other in density. The algorithm is introduced as follows:

DBSCAN (Density-Based Spatial Clustering of Applications with Noise, density-based clustering method with noise) is a typical Density clustering algorithm, and the basic concept involved is as follows:

1. epsilon-neighborhood: for xj ε D, its ε -neighborhood contains the sub-sample set in sample set D that is no more than ε away from xj.

2. Core object: for any sample xj e D, if N e (xj) corresponding to its e-neighborhood contains at least MinPts samples, i.e., if |N e (xj) |gtoreq MinPts, xj is the core object.

3. The density is direct: if xi is located in the E-neighborhood of xj and xj is the core object, then xi is said to be directly reached by xj density.

4. The density can be achieved: for xi and xj, if there are sample sequences p1, p2,..pt satisfies p1=xi, pt=xj, and pt+1 is directly reached by pT density, then xj is said to be reachable by xi density. That is, the density can be satisfied with the transferability.

5. Density connection: for xi and xj, if there is a core object sample xk, let both xi and xj be reachable by xk density, then we call xi and xj density connected.

DBSCAN requires two parameters: epsilon (eps) and the minimum number of points (minPts) needed to form a high density region, starting with an arbitrary point that is not accessed, then exploring the epsilon-neighborhood of this point, if there are enough points in the epsilon-neighborhood, creating a new cluster, otherwise this point is labeled as noise. Note that this point may then be found in the e-neighborhood of other points, and that the e-neighborhood may have enough points at which time this point will be added to the cluster.

If a point is located in a dense region of a cluster, its e-neighborhood points also belong to the cluster, and when these new points are added to the cluster, if it(s) are also in the dense region, its e-neighborhood point(s) are also added to the cluster. This process is repeated until no more points can be added, so that a densely connected cluster is completely found. Then, an unaccessed point will be explored to find a new cluster or noise.

The DBSCAN algorithm can be abstracted into the following steps:

1. finding out the points in the E-neighborhood of each point, and finding out the core points with more than minPts neighborhood.

2. The connected components of the core points are found on the adjacent graph, and all non-core points are ignored.

3. And (3) each non-core point is allocated to nearby epsilon neighbor clusters, and if not, the non-core points are allocated to noise.

In some embodiments, determining the azimuth of the base station antenna based on the coverage sector of the base station antenna in combination with MR data within the sector comprises:

As shown in FIG. 2, an MR data rasterization process is also included in embodiments of the present disclosure.

As an example, for computational efficiency and geographical presentation, MR data is rasterized according to longitude and latitude, as follows:

Referring to fig. 4, an mr data rasterization schematic diagram is shown. The longitudinal direction of the earth is divided into large grids in units of 6 longitudes and the transverse direction is divided into large grids in units of 3 latitudes, and each large grid is a large area and is represented by earth_id. Each large area is divided into small grids according to different grid side lengths (e.g. 20 meters) by taking the center as an origin, and x_offset and y_offset are coordinates of each small grid in the large area, namely three values of earth_id, x_offset and y_offset can determine each grid on the earth.

In the foregoing, based on the base station ID and the sector ID, the industrial parameter data and the MR data are associated, specifically, the MR raster data and the industrial parameter data are associated, and the AGPS MR raster corresponding to each sector is obtained by associating the AGPS MR raster data and the industrial parameter data through the base station ID and the sector ID fields.

As shown in fig. 5, in the sector covered by the antenna, the RSRP value is larger in the MR near the antenna azimuth axis among MR points close to the base station. The color shading at the points in fig. 5 represents RSRP intensity. The point A is the base station position, and the line AB is the antenna azimuth facing direction.

As an example, in the foregoing, the specific procedure for measuring azimuth angle is as follows:

mr data clustering and filtering:

And clustering the MR grids under the sector by using a DBSCAN algorithm according to longitude and latitude, reserving clustering core points and non-core points, and eliminating the external points (noise).

2. Azimuth calculation:

(1) the grids in the coverage area of the sector are sorted from small to large according to the distance between the grids and the base station, and are divided into a plurality of distance intervals with the same number;

(2) within each distance interval, the weight of each grid is calculated according to the characteristics of the grid, such as the average RSRP value and the number of MR contained in the grid, and the calculation formula is as follows:

w＝rsrp×(log(cnt)+1) (1)

where w represents the weight of each grid, RSRP represents the average RSRP value, cnt represents the number of MR contained in the grid.

(3) Determining a reference point in grids contained in the distance interval according to the weight of each grid;

(4) an azimuth angle of the base station antenna is determined based on the location of the reference point and the location of the base station.

The reference point may be a grid with the greatest weight in each distance interval.

As one example, determining the azimuth of the base station antenna based on the location of the reference point and the location of the base station may include:

Here, the azimuth angle between the base station and the reference point is first calculated.

Let the coordinates of the base station and the reference point be (x) ₁ ,y ₁ ) And (x) ₂ ,y ₂ ) The azimuth angle α can be calculated by the following formula:

α＝atan2(x ₂ -x ₁ ,y ₂ -y ₁ ) (2)

the predicted azimuth, i.e. the actual azimuth of the base station antenna, can then be calculated from the average of the base station and the reference point azimuth.

In some embodiments, after obtaining the azimuth of the base station antenna, the azimuth correction list may be further output, and the antenna azimuth in the parameter data may be calibrated based on the azimuth of the base station antenna.

As an example, the predicted azimuth angle and the azimuth angle of the industrial parameter sector are compared according to the following formula, when the angle deviation is larger than delta, the azimuth angle of the sector in the basic database is judged to be inconsistent with the actual installation azimuth angle on site, an azimuth angle correction list is output, and industrial parameter calibration is carried out according to the predicted actual azimuth angle.

Prediction angle-reference sector azimuth angle | > delta (delta is the angular deviation threshold)

The RSRP is an important characteristic of MR data, a strong correlation exists between the spatial distribution of the RSRP value and the actual azimuth of the sector, and the method is more accurate than a common prediction method through measuring and calculating the azimuth of the sector by the MR position processed by the RSRP value of the MR and the AI big data machine learning algorithm.

By the method provided by the embodiment of the disclosure, the automatic checking and calibration of the antenna azimuth angle can be realized, the accuracy of basic data management is improved, the wireless network planning and the optimizing work are accurately enabled to be carried out, a large amount of manual testing cost is saved, the cost reduction and synergy are realized, and the method has the characteristics of high updating frequency, high efficiency and high accuracy.

For ease of understanding, the method of measuring antenna azimuth in the present disclosure will be described in detail below with reference to the accompanying drawings as a specific example.

Clustering MR grids under the sector according to longitude and latitude by using a DBSCAN algorithm, selecting parameters E=0.01 and minPts=5, and eliminating the external points.

As shown in fig. 6, the grids in the coverage area of the sector are sorted from small to large according to the distance between the grids and the base station, and the grids are equally divided into 10 distance intervals after weight removal.

Within each distance interval, the weight (w) of each grid is calculated according to the average RSRP value (RSRP) of the grid and the MR number (cnt) contained in the grid, and the mode is calculated according to the formula (1) in the foregoing.

Selecting a grid with the largest weight in each distance interval as a reference point, and calculating azimuth angles between the base station and the reference point, wherein five-pointed star is used for calculating the reference point for the azimuth angle with the largest weight in each distance interval in FIG. 7;

The predicted azimuth angle is calculated according to the average value of the azimuth angles of the base station and the reference point, and as shown in fig. 8, the midpoint M is the base station position, and the line segment direction is the predicted azimuth angle, namely the azimuth angle of the base station antenna.

According to the method, the device and the system, the MR measurement information and the base station position information of a large number of mobile phone terminals are collected, the characteristic of the spatial distribution of the RSRP intensity of the 4G MR is utilized, an AI big data machine learning algorithm is combined, an accurate antenna azimuth angle is obtained, then the antenna azimuth angle is compared with the antenna azimuth angle in engineering parameters for analysis, automatic deviation correction of the antenna azimuth angle in the engineering parameters is achieved, the basic data management accuracy is improved, and the wireless network planning and optimizing work is accurately enabled.

Based on the same inventive concept, the embodiments of the present disclosure also provide an apparatus for measuring and calculating an antenna azimuth, as described in the following embodiments. Since the principle of solving the problem of the embodiment of the device is similar to that of the embodiment of the method, the implementation of the embodiment of the device can be referred to the implementation of the embodiment of the method, and the repetition is omitted.

Fig. 9 shows an apparatus for measuring an azimuth angle of an antenna according to an embodiment of the present disclosure, as shown in fig. 6, the apparatus 900 for measuring an azimuth angle of an antenna includes:

a data obtaining module 902, configured to obtain the parameter data of the base station antenna and measurement report MR data of the terminal, where the MR data includes reference signal received power RSRP;

The azimuth measuring module 904 is configured to determine an azimuth of the base station antenna based on the parameter data of the base station antenna and the measurement report MR data of the terminal, in combination with the relationship between RSRP and the antenna distance and angle.

In some embodiments, azimuth measurement module 904 may include:

the sector determining unit is used for determining a coverage sector of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal by combining the relation between RSRP and the antenna distance and angle;

and the azimuth angle determining unit is used for determining the azimuth angle of the base station antenna based on the coverage sector of the base station antenna and combining the MR data in the sector.

Accordingly, the sector determining unit may be specifically implemented as follows:

Accordingly, the azimuth measurement module 904 may further include:

and the data association unit is used for associating the industrial parameter data and the MR data based on the base station ID and the sector ID before determining the coverage sector of the base station antenna by combining the relation between the sector position, the sector transmitting power and the RSRP and the antenna distance and angle based on the distribution diagram of the MR data.

In some embodiments, the MR data is aggregated based on the terminal location, which may be implemented using a DBSCAN algorithm.

In some embodiments, the azimuth determination unit may be embodied as follows:

In some embodiments, determining the azimuth of the base station antenna based on the location of the reference point and the location of the base station may include:

In some embodiments, the apparatus 900 for measuring antenna azimuth may further include:

and the engineering reference calibration module is used for calibrating the azimuth angle of the antenna in engineering reference data based on the azimuth angle of the base station antenna.

The device for measuring and calculating the antenna azimuth angle provided by the embodiment of the application can be used for executing the method for measuring and calculating the antenna azimuth angle provided by the embodiment of the method, and the implementation principle and the technical effect are similar, so that the description is omitted herein for brevity.

Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.

An electronic device 1000 according to such an embodiment of the present disclosure is described below with reference to fig. 10. The electronic device 1000 shown in fig. 10 is merely an example and should not be construed as limiting the functionality and scope of use of the disclosed embodiments.

As shown in fig. 10, the electronic device 1000 is embodied in the form of a general purpose computing device. Components of electronic device 1000 may include, but are not limited to: the at least one processing unit 1010, the at least one memory unit 1020, and a bus 1030 that connects the various system components, including the memory unit 1020 and the processing unit 1010.

Wherein the storage unit stores program code that is executable by the processing unit 1010 such that the processing unit 1010 performs steps according to various exemplary embodiments of the present disclosure described in the above section of the present specification. For example, the processing unit 1010 may perform the method embodiments described above as follows:

In some embodiments, the processing unit 1010 may also be configured to perform:

Accordingly, the processing unit 1010 may also be configured to perform:

based on the distribution diagram of MR data, the reference data and MR data are related based on the base station ID and the sector ID before the coverage sector of the base station antenna is determined by combining the relation between the sector position, the sector transmitting power and the RSRP and the antenna distance and angle.

The memory unit 1020 may include readable media in the form of volatile memory units such as Random Access Memory (RAM) 10201 and/or cache memory unit 10202, and may further include Read Only Memory (ROM) 10203.

The storage unit 1020 may also include a program/utility 10204 having a set (at least one) of program modules 10205, such program modules 10205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.

Bus 1030 may be representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 1000 can also communicate with one or more external devices 1040 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 1000, and/or with any device (e.g., router, modem, etc.) that enables the electronic device 1000 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 1050. Also, electronic device 1000 can communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 1060. As shown, the network adapter 1060 communicates with other modules of the electronic device 1000 over the bus 1030. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with the electronic device 1000, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, a computer-readable storage medium, which may be a readable signal medium or a readable storage medium, is also provided. On which a program product is stored which enables the implementation of the method described above of the present disclosure. In some possible implementations, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.

More specific examples of the computer readable storage medium in the present disclosure may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

In this disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Alternatively, the program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

In particular implementations, the program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.

Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order or that all illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.

From the description of the above embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A method of measuring antenna azimuth, the method comprising:

and determining the azimuth angle of the base station antenna by combining the relation between RSRP and the antenna distance and angle based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal.

2. The method of claim 1, wherein the determining the azimuth angle of the base station antenna based on the parameter data of the base station antenna and the measurement report MR data of the terminal in combination with the RSRP versus antenna distance and angle comprises:

and determining the azimuth angle of the base station antenna based on the coverage sector of the base station antenna and combining the MR data in the sector.

3. The method of claim 2, wherein the process data includes sector location and sector transmit power, and the MR data further includes terminal location; the determining the coverage sector of the base station antenna based on the parameter data of the base station antenna and the measurement report MR data of the terminal and combining the relation between the RSRP and the antenna distance and angle comprises the following steps:

and determining a coverage sector of the base station antenna based on the distribution diagram of the MR data by combining the sector position, the sector transmitting power and the relation between the RSRP and the antenna distance and angle.

4. The method of claim 3, wherein the industrial parameter data further comprises a base station ID and a sector ID, and wherein the MR data further comprises a base station ID and a sector ID; before determining the coverage sector of the base station antenna based on the distribution diagram of the MR data and combining the sector position, the sector transmitting power and the relation between the RSRP and the antenna distance and angle, the method further comprises:

the parameter data and the MR data are associated based on the base station ID and the sector ID.

5. A method according to claim 3, wherein said aggregating said MR data based on said terminal position comprises:

6. The method of claim 2, wherein the determining the azimuth angle of the base station antenna based on the coverage sector of the base station antenna in combination with the MR data in the sector comprises:

Rasterizing an image corresponding to a coverage sector of the base station antenna to obtain a plurality of grids;

dividing the grids into a plurality of distance intervals according to the distance between each grid and the base station;

and determining the azimuth angle of the base station antenna based on the position of the reference point and the position of the base station.

7. The method of claim 6, wherein the determining the azimuth of the base station antenna based on the location of the reference point and the location of the base station comprises:

and determining the azimuth angles of the base station antennas according to the first azimuth angles.

8. The method according to any one of claims 1-7, further comprising:

and calibrating the azimuth angle of the antenna in the industrial parameter data based on the azimuth angle of the base station antenna.

9. An apparatus for measuring antenna azimuth angle, said apparatus comprising:

And the azimuth angle measuring and calculating module is used for determining the azimuth angle of the base station antenna based on the industrial parameter data of the base station antenna and the measurement report MR data of the terminal and combining the relation between the RSRP and the antenna distance and angle.

10. An electronic device, comprising:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the method of measuring antenna azimuth of any one of claims 1-8 via execution of the executable instructions.

11. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the method of measuring antenna azimuth according to any one of claims 1-8.