CN116828518A

CN116828518A - Method and device for positioning uplink frequency band interference source, electronic equipment and storage medium

Info

Publication number: CN116828518A
Application number: CN202210262102.5A
Authority: CN
Inventors: 赵春芹; 徐剑
Original assignee: Shanghai Datang Mobile Communications Equipment Co ltd
Current assignee: Shanghai Datang Mobile Communications Equipment Co ltd
Priority date: 2022-03-16
Filing date: 2022-03-16
Publication date: 2023-09-29

Abstract

The embodiment of the application provides a method, a device, electronic equipment and a storage medium for positioning an uplink frequency band interference source, wherein the method comprises the following steps: based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance index, obtaining an interfered cluster by clustering the interfered cells; and determining the position of the interference source in the target area based on the interfered cluster. According to the method, the device, the electronic equipment and the storage medium for locating the interference source of the uplink frequency band, disclosed by the embodiment of the application, the position of the suspected interference source can be rapidly identified by analyzing the industrial parameter data and the uplink interference statistical performance KPI data of the base station in the existing communication network and adopting an interference source locating algorithm, the investigation range is reduced, and the efficiency of locating the interference source which interferes with the uplink frequency band is improved.

Description

Method and device for positioning uplink frequency band interference source, electronic equipment and storage medium

Technical Field

The present application relates to the field of communications technologies, and in particular, to a method, an apparatus, an electronic device, and a storage medium for locating an uplink frequency band interference source.

Background

Along with the continuous evolution of network systems, the network construction scale is continuously enlarged, and the coexistence of multiple systems and multiple frequency bands is a common phenomenon. At the same time, the probability of inter-system or inter-frequency band interference is also greatly increased, which increases the risk of affecting the performance and quality of the communication network. The uplink frequency band interference is one of key factors affecting the performance and quality of the communication network, and has significant effects on the operation quality, handover, congestion, and coverage and capacity of the communication network. The influence of external uplink interference is particularly prominent, and can have a large negative influence on user experience and user perception.

The conventional interference checking is mainly to find an interference source by a road fixed-point Test such as DT/CQT (Drive Test/Call Quality Test) and a sweep frequency method. The disadvantage is that the required manpower and time costs are huge and the timeliness is poor. Or by graphic processing means such as desktop geographic information system software. The disadvantage is that the accuracy is often lower without the efficient support of the existing communication network data, simply by geographical distribution.

Disclosure of Invention

The embodiment of the application provides a method, a device, electronic equipment and a storage medium for positioning an uplink frequency band interference source, which are used for solving the defects of higher labor cost and time cost and lower accuracy required by positioning the interference source which causes interference to an uplink frequency band in the prior art and realizing efficient and accurate positioning of the uplink frequency band interference source.

In a first aspect, an embodiment of the present application provides a method for locating an uplink frequency band interference source, including:

based on the industrial parameter data of the base station in the target area and the uplink interference statistical performance KPI (Key Performance Indicator, key performance index) data, obtaining an interfered cluster by clustering the interfered cells;

and determining the position of the interference source in the target area based on the interfered cluster.

Optionally, according to the method for positioning an uplink frequency band interference source in an embodiment of the present application, the obtaining the interfered cluster by clustering the interfered cell based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance indicator includes:

dividing the target area into a plurality of grids having a predetermined area;

constructing a Thiessen polygon by taking a base station as a discrete point based on the industrial parameter data of the base station;

Determining the interfered cells from the cells of the target area based on the uplink interference statistical performance KPI data;

determining the number of grids which can be covered by an interference source based on the area of the grids and the industrial parameter data of the base station;

and clustering the interfered cells by using a K-means++ (modified K-Means clustering algorithm) clustering algorithm based on the positions of the interfered cells, wherein the class which is formed by the interfered cells and is clustered again, wherein the number of the grids covered by the class is larger than that of the grids which can be covered by the interference source, and finally the interfered clusters with the number of the grids covered by the class being smaller than or equal to that of the grids which can be covered by the interference source are obtained.

Optionally, the method for locating an uplink frequency band interference source according to one embodiment of the present application, wherein determining the interfered cell from each cell in the target area based on the uplink interference statistical performance KPI data includes:

based on the uplink interference statistical performance KPI data, obtaining the average interference level and the number of times of interference received by a first cell;

and determining the first cell as an interfered cell under the condition that the average interference level of the first cell is larger than a first threshold and the number of times of interference received by the first cell is larger than or equal to a second threshold.

Optionally, according to a method for locating an uplink frequency band interference source according to an embodiment of the present application, the determining, based on the area of the grid and the parameter data of the base station, the number of grids that the interference source can cover includes:

determining the signal coverage area of a cell based on the industrial parameter data of the base station and the Thiessen polygon where the base station is located;

and determining the number of grids which can be covered by the interference source based on the signal coverage area of the cells, the number of cells which can be affected by the interference source and the area of the grids.

Optionally, the method for locating an uplink frequency band interference source according to one embodiment of the present application, the clustering the interfered cells using a K-means++ clustering algorithm includes:

and determining the number of centroids which enable the average profile coefficient of the clustering result of the interfered cells to be maximum as K, wherein K is the number of total centroids selected in the process of clustering the interfered cells by using a K-means++ clustering algorithm.

Optionally, the method for locating an uplink frequency band interference source according to an embodiment of the present application, the dividing the target area into a plurality of grids with predetermined areas includes:

The target area is divided into a plurality of square grids of 50 meters in length.

Optionally, the method for locating an uplink frequency band interference source according to an embodiment of the present application, wherein determining, based on the interfered cluster, a location of the interference source in the target area includes:

screening out a grid set positioned in an interfered cell in a first interfered cluster;

based on the distance ratio vector and the interference level ratio vector of each grid in the grid set, obtaining the Euclidean distance between each grid in the grid set and the interference source;

and determining the grid with the shortest Euclidean distance with the interference source as the position of the interference source.

Optionally, according to a method for positioning an uplink frequency band interference source according to an embodiment of the present application, the obtaining, based on the distance ratio vector and the interference level ratio vector of each grid in the grid set, the euclidean distance between each grid in the grid set and the interference source includes:

obtaining a distance ratio vector of each grid based on the ratio of the distance from each grid to the base station of each interfered cell to the distance from each grid to the base station of the interfered cell with the highest interference level;

Obtaining the interference level ratio vector based on the ratio of the interference level of each interfered cell to the interference level of the interfered cell with the highest interference level;

and obtaining Euclidean distances between each grid and the interference source based on the distance ratio vector and the interference level ratio vector of each grid.

Optionally, according to a method for positioning an uplink frequency band interference source according to an embodiment of the present application, the obtaining, based on the distance ratio vector and the interference level ratio vector of each grid, the euclidean distance between each grid and the interference source includes:

and regarding the dimension of each element in the distance ratio vector of the first grid as being in the same dimension as the corresponding element in the interference level ratio vector, solving the difference between each element in the distance ratio vector and the corresponding element in the interference level ratio vector, solving the sum of squares of each difference, and squaring the sum to obtain the Euclidean distance between each grid and the interference source.

In a second aspect, an embodiment of the present application further provides an electronic device, including a memory, a transceiver, and a processor, where:

A memory for storing a computer program; a transceiver for transceiving data under control of the processor; a processor for reading the computer program in the memory and performing the following operations:

based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance index, obtaining an interfered cluster by clustering the interfered cells;

Optionally, according to an embodiment of the present application, the obtaining, by clustering the interfered cells, the interfered cluster based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance indicator includes:

dividing the target area into a plurality of grids having a predetermined area;

And clustering the interfered cells by using a K-means++ clustering algorithm based on the positions of the interfered cells, wherein the class formed by the interfered cells with the number of the covered grids being larger than that of the grids which can be covered by the interference source is clustered again, and finally the interfered clusters with the number of the covered grids being smaller than or equal to that of the grids which can be covered by the interference source are obtained.

Optionally, according to the electronic device of one embodiment of the present application, the determining, based on the uplink interference statistical performance KPI data, the interfered cell from each cell of the target area includes:

Optionally, according to the electronic device of one embodiment of the present application, the determining, based on the area of the grid and the parameter data of the base station, the number of grids that can be covered by the interference source includes:

Optionally, the electronic device according to an embodiment of the present application, the clustering the interfered cells using a K-means++ clustering algorithm includes:

Optionally, according to an embodiment of the present application, the dividing the target area into a plurality of grids having a predetermined area includes:

Optionally, according to an embodiment of the present application, the determining, based on the interfered cluster, a location of an interference source in the target area includes:

Optionally, according to an embodiment of the present application, the obtaining, based on the distance ratio vector and the interference level ratio vector of each grid in the grid set, the euclidean distance between each grid in the grid set and the interference source includes:

Optionally, according to the electronic device of one embodiment of the present application, the obtaining, based on the distance ratio vector and the interference level ratio vector of each grid, a euclidean distance between each grid and the interference source includes:

In a third aspect, an embodiment of the present application provides an apparatus for locating an uplink frequency band interference source, including:

the interference cell clustering unit is used for obtaining an interfered cluster by clustering the interfered cells based on the industrial parameter data of the base stations in the target area and the key performance indicator KPI data of the uplink interference statistics performance;

and the interference source positioning unit is used for determining the position of the interference source in the target area based on the interfered cluster.

In a fourth aspect, embodiments of the present application further provide a processor-readable storage medium storing a computer program for causing the processor to perform the steps of the method for locating an interference source in an uplink frequency band as described in the first aspect.

According to the method, the device, the electronic equipment and the storage medium for locating the interference source of the uplink frequency band, disclosed by the embodiment of the application, the position of the suspected interference source can be rapidly identified by analyzing the industrial parameter data and the uplink interference statistical performance KPI data of the base station in the existing communication network and adopting an interference source locating algorithm, the investigation range is reduced, and the efficiency of locating the interference source which interferes with the uplink frequency band is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow chart of a method for locating an uplink frequency band interference source according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a base station as a discrete point to construct a Thiessen polygon according to an embodiment of the present application;

fig. 3 is a schematic flow chart of clustering interfered cells to obtain an interfered cluster according to an embodiment of the present application;

Fig. 4 is a schematic diagram of distances from each grid to a base station to which each interfered cell belongs according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of an apparatus for locating an uplink frequency band interference source according to an embodiment of the present application.

Detailed Description

In the embodiment of the application, the term "and/or" describes the association relation of the association objects, which means that three relations can exist, for example, a and/or B can be expressed as follows: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.

The term "plurality" in embodiments of the present application means two or more, and other adjectives are similar.

The technical scheme provided by the embodiment of the application can be suitable for various systems, in particular to a 5G system. For example, suitable systems may be global system for mobile communications (global system of mobile communication, GSM), code division multiple access (code division multiple access, CDMA), wideband code division multiple access (Wideband Code Division Multiple Access, WCDMA) universal packet Radio service (general packet Radio service, GPRS), long term evolution (long term evolution, LTE), LTE frequency division duplex (frequency division duplex, FDD), LTE time division duplex (time division duplex, TDD), long term evolution-advanced (long term evolution advanced, LTE-a), universal mobile system (universal mobile telecommunication system, UMTS), worldwide interoperability for microwave access (worldwide interoperability for microwave access, wiMAX), 5G New air interface (New Radio, NR), and the like. Terminal devices and network devices are included in these various systems. Core network parts such as evolved packet system (Evloved Packet System, EPS), 5G system (5 GS) etc. may also be included in the system.

The terminal device according to the embodiment of the present application may be a device that provides voice and/or data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem, etc. The names of the terminal devices may also be different in different systems, for example in a 5G system, the terminal devices may be referred to as User Equipment (UE). The wireless terminal device may communicate with one or more Core Networks (CNs) via a radio access Network (Radio Access Network, RAN), which may be mobile terminal devices such as mobile phones (or "cellular" phones) and computers with mobile terminal devices, e.g., portable, pocket, hand-held, computer-built-in or vehicle-mounted mobile devices that exchange voice and/or data with the radio access Network. Such as personal communication services (Personal Communication Service, PCS) phones, cordless phones, session initiation protocol (Session Initiated Protocol, SIP) phones, wireless local loop (Wireless Local Loop, WLL) stations, personal digital assistants (Personal Digital Assistant, PDAs), and the like. The wireless terminal device may also be referred to as a system, subscriber unit (subscriber unit), subscriber station (subscriber station), mobile station (mobile), remote station (remote station), access point (access point), remote terminal device (remote terminal), access terminal device (access terminal), user terminal device (user terminal), user agent (user agent), user equipment (user device), and embodiments of the present application are not limited in this respect.

The network device according to the embodiment of the present application may be a base station, where the base station may include a plurality of cells for providing services for the terminal. A base station may also be called an access point or may be a device in an access network that communicates over the air-interface, through one or more sectors, with wireless terminal devices, or other names, depending on the particular application. The network device may be operable to exchange received air frames with internet protocol (Internet Protocol, IP) packets as a router between the wireless terminal device and the rest of the access network, which may include an Internet Protocol (IP) communication network. The network device may also coordinate attribute management for the air interface. For example, the network device according to the embodiment of the present application may be a network device (Base Transceiver Station, BTS) in a global system for mobile communications (Global System for Mobile communications, GSM) or code division multiple access (Code Division Multiple Access, CDMA), a network device (NodeB) in a wideband code division multiple access (Wide-band Code Division Multiple Access, WCDMA), an evolved network device (evolutional Node B, eNB or e-NodeB) in a long term evolution (long term evolution, LTE) system, a 5G base station (gNB) in a 5G network architecture (next generation system), a home evolved base station (Home evolved Node B, heNB), a relay node (relay node), a home base station (femto), a pico base station (pico), etc., which are not limited in the embodiment of the present application. In some network structures, the network device may include a Centralized Unit (CU) node and a Distributed Unit (DU) node, which may also be geographically separated.

Multiple-input Multiple-output (Multi Input Multi Output, MIMO) transmissions may each be made between a network device and a terminal device using one or more antennas, and the MIMO transmissions may be Single User MIMO (SU-MIMO) or Multiple User MIMO (MU-MIMO). The MIMO transmission may be 2D-MIMO, 3D-MIMO, FD (Full Dimension) -MIMO or massive-MIMO, diversity transmission, precoding transmission, beamforming transmission, or the like, depending on the form and number of the root antenna combinations.

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

Fig. 1 is a flowchart of a method for locating an uplink frequency band interference source according to an embodiment of the present application, as shown in fig. 1, an application embodiment provides a method for locating an uplink frequency band interference source, where an execution body of the method may be an electronic device, for example, a computer or a computer mounted on a cloud. The method comprises the following steps:

Step 110, obtaining an interfered cluster by clustering the interfered cells based on the industrial parameter data of the base stations in the target area and the key performance indicator KPI data of the uplink interference statistics performance.

Specifically, in the embodiment of the application, firstly, the industrial parameter data and the uplink interference statistical performance KPI data of each base station in the wireless communication network of the target area are obtained. The target area is an area to be located by an interference source, in which an uplink frequency band is generally interfered, especially a cell interfered by the outside, and the communication quality of the terminal user served by the interfered cell is reduced. The location of the base station (e.g., expressed in terms of latitude and longitude), the signal coverage of the base station, the coverage direction of the cell, etc., are included in or available from the base station's reference data. For example, the base station's industrial parameters include the industrial parameters of the base station antenna, which mainly include altitude, pitch angle, azimuth angle, position, etc., and these parameters have a decisive influence on the electromagnetic coverage of the base station. For example, too high an antenna may cause too much coverage of the base station, resulting in a large traffic volume for the base station, while a base station adjacent to the base station may not be able to perform its function due to the smaller coverage and coverage by the base station, resulting in an unbalanced traffic volume. The antenna pitch angle affects the electromagnetic wave energy overlap condition of the cell boundary and the surrounding cells and the shape of the coverage area of the antenna. The location of an antenna, i.e. the location of a base station, which typically has multiple antennas, affects the signal coverage of the base station and the coverage direction of the cell. The uplink interference statistical performance KPI data includes or can be obtained from whether each cell has uplink interference, the interference degree, and the like. And then based on the industrial parameter data and the uplink interference statistical performance KPI data of each base station in the wireless communication network of the target area, obtaining an interfered cluster comprising the interfered cell through cluster analysis. Cluster analysis refers to an analysis process of grouping a collection of physical or abstract objects into multiple classes composed of similar objects, and the interfered cells have regional aggressor property because in wireless communication interfered by external uplink frequency bands, an interference source affects multiple cells nearby the interference source. The statistical cluster analysis method comprises a systematic cluster method, a decomposition method, an addition method, a dynamic cluster method, ordered sample clustering, overlapping clustering, fuzzy clustering and the like. Cluster analysis may be performed using cluster analysis tools that employ k-means, k-center points, etc. algorithms.

And 120, determining the position of the interference source in the target area based on the interfered cluster.

Specifically, in the embodiment of the present application, after obtaining the interfered cluster including the interfered cell, a specific location (for example, expressed by longitude and latitude) or a relatively small location range where the interference source is located may be further determined according to the interfered cluster. Generally, according to the propagation principle of a wireless link and a wireless signal, under the same propagation model, the closer the distance between the wireless link and an interference source is, the stronger the intensity of interference of a communication signal is. The distance between the interference source and the cell has similarity with the received interference level of the interfered cell, and the higher the similarity is, the more likely the interference source appears, so that an interference source positioning algorithm can be designed to predict the possible position of the interference source.

According to the method for positioning the uplink frequency band interference source, disclosed by the embodiment of the application, the uplink interference receiving cell in the communication network is identified based on the industrial parameter data and the uplink interference statistical performance KPI data, then the uplink interference receiving cluster is identified through the continuous clustering algorithm, and the suspected interference source position is output through the interference positioning algorithm. The range of uplink interference check is reduced, and the efficiency of interference check is improved.

Optionally, the obtaining the interfered cluster by clustering the interfered cells based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance index includes:

dividing the target area into a plurality of grids having a predetermined area;

Specifically, a GIS (Geographic Information System ) map including communication network information of a target region is first acquired, and then the entire GIS map is divided into grids having a predetermined area. GIS data represents real world objective objects (e.g., geographic and communication networks) in the form of digital data, which may include discrete objects (e.g., base stations) that are primarily stored in a GIS system as a grid, the grid data being comprised of rows and columns that store unique value storage elements. Typically the storage unit represents a square area of the ground but may be used to represent other shapes.

Fig. 2 is a schematic diagram of a principle of constructing a Thiessen polygon by using a base station as a discrete point according to an embodiment of the present application, and referring to fig. 2, after a GIS map including communication network information of a target area is obtained, the base station is used as the discrete point to construct the Thiessen polygon, wherein the position of the base station is marked on the GIS map according to the industrial parameter data of the base station. A Thiessen polygon, also called Feng Luo Nor, is a subdivision of the space plane, and is characterized by any location within a polygon that is closest to the discrete point of the polygon (the point where the base station is located), that is far from the discrete point within an adjacent polygon, and that contains only one discrete point within each polygon.

And judging whether each cell has uplink interference according to the uplink interference statistical performance KPI data, and determining the interfered cell. The step of determining the interfered cell may be performed before, simultaneously with, or after the steps of dividing the GIS map into grids and constructing the tesen polygon, and may be determined before performing cluster analysis on the interfered cell. The uplink interference statistical performance KPI data includes or can be obtained from whether each cell has uplink interference, the interference degree, and the like.

Optionally, the determining the interfered cell from each cell of the target area based on the uplink interference statistical performance KPI data includes:

based on the uplink interference statistical performance KPI data, obtaining the average interference level (the unit can be [ dBm ]) of the first cell and the number of times of interference received;

Specifically, there are a plurality of cells in the target area, and a certain cell is referred to as a first cell for convenience of description, whether each cell is an interfered cell may be determined using the same method as that for determining whether the first cell is an interfered cell. The first threshold is used for comparison with the average interference level of the cell, and may also be in units of [ dBm ], which may be predetermined or determined according to some rule. The second threshold is used for comparing the number of times of interference received by the cell, and judging that the cell has uplink interference and determining the cell as the interfered cell when the average interference level of the cell is larger than the first threshold and the number of times of interference received by the cell is larger than or equal to the second threshold.

Fig. 3 is a schematic flow chart of clustering interfered cells to obtain an interfered cluster according to an embodiment of the present application, and referring to fig. 3, clustering the interfered cells to obtain the interfered cluster includes the following steps.

First, in step 310, the number of grids that the interfering source can cover is determined.

The number of grids that can be covered by the interference source is obtained by dividing the area of the grids by the range (area) that can be covered by the interference source.

Optionally, the determining, based on the area of the grid and the parameter data of the base station, the number of grids that can be covered by the interference source includes:

Specifically, according to the industrial parameter data of the base station, the angle range of the coverage direction of the cell can be obtained, the coverage area of the cell can be regarded as a sector which takes the base station as a radiation point and radiates outwards, and then according to the Thiessen polygon where the base station is located, the radiation boundary of the cell can be determined, for example, the signal coverage area of the cell is defined by a pattern formed by the sector and the Thiessen polygon.

The signal coverage area of the cells is multiplied by the number of cells which can be affected by the interference source to obtain the area which can be covered by the interference source, and the area of the grids is divided to obtain the number of grids which can be covered by the interference source. For example, the coverage area of the obtained cell is based on the industrial parameter data of the base stationThe covering radius R is oneTypically 350 meters; the interference source affects a positive integer of n, typically 6 to 10; then it is determined that the number of grids that the interfering source can cover is +.>

Then, step 320, clusters the interfered cells.

The method comprises the steps of obtaining the position (expressed by longitude and latitude for example) of an interfered cell, and adopting a K-means++ clustering algorithm to perform primary clustering on the interfered cell, wherein the purpose is to divide the whole network interfered cell into large categories according to the geographical position of the cell; let longitude and latitude of interfered cell be x _i (i is between 1 and N, N is the number of data) such that each x _i Is a 2-dimensional column vector; the original data is normalized by 0-1, and the normalization formula is as follows:x _min is x _i Minimum value of x _max Is x _i A medium maximum value;

the K-means++ algorithm is an improved version based on the K-Means algorithm, which uses the Euclidean geometric distance as a measure formula: for i=1, 2..m, sample x is calculated _i And the respective centroid vector mu _j Distance of (j=1, 2,..k):the K-Means algorithm first needs to complete before formal clustering, namely initializing K cluster centers by Means of, for example, random allocation. The K-means++ algorithm adopts the maximum interval principle to distribute the K cluster centers, so that the convergence speed of the algorithm can be increased, and for each point x in the data set _i Calculate its distance from nearest cluster center among the selected cluster centers +.>Where r=1, 2,.. _selected 。k _selected For the number of centroids selected.

Optionally, the clustering the interfered cells using a K-means++ clustering algorithm includes:

Specifically, the value range of K is determined according to the amount of interference data: for example, in the range of 10 to 100, selecting integers with interval of 5 as candidate values of K, respectively calculating average contour coefficients, and selecting the value of K corresponding to the average contour coefficient closest to 1; the contour coefficient calculation method comprises the following steps:

the similarity between the sample and other samples in the cluster where the sample is located is recorded as a, and the value of the similarity is equal to the average distance between the sample and all other points in the same cluster; the similarity of the sample to samples in other clusters is noted as b, whose value is equal to the average distance between the sample and all points in the next nearest cluster. According to the clustering requirement that the intra-cluster difference is small and the cluster heterodyne is large, we hope that b is always larger than a and the more large is better;

From which individual samples can be obtainedThe evaluation index of the value of K is the contour coefficient mean value of all the sample points.

Next, in step 330, it is determined whether the number of grids covered in the class is greater than the number of grids that the interference source can cover.

Specifically, first, the number M of grids covered in each category is calculated _i If the number M of grids covered in the class _i And if the number of the grids which can be covered by the interference source is smaller than or equal to the number X of the grids, determining the type as an interfered cluster, and coding the cluster, namely, marking a cluster number. Otherwise, i.e. if the number of grids covered within a class M _i Greater than the number of grids X that the interfering source can cover, proceed to step 340 where the class is processed again using the K-means++ clustering algorithm and the clusters that are again clustered are encoded.

In this clustering analysis, byWill (M) _i And X) rounding to obtain the value of K. Finally, in step 350, the number of the covered grids is smaller than or equal to the number of the grids which can be covered by the interference source, the interfered cells grouped by the clusters are output, and the cluster numbers are marked.

Optionally, the determining, based on the interfered cluster, a location of an interference source in the target area includes:

Specifically, based on the principle that the higher the intensity of the interference signal received by the cell is, the closer the distance between the cell and the interference source is, according to the distance ratio between each grid in the signal coverage range of the cell and the interference cell and the ratio between each grid and the interference level, similarity matching is performed, so that the most possible position of the interference source is predicted. For example, assuming that an interfered cluster has only two interfered cells, denoted as cell 1 and cell 2, respectively, if the interference levels of cell 1 and cell 2 are relatively close, then the most likely location of the interfering source may be in a position intermediate the positions of the two interfered cells. If there is a cell 1 receiving an interference signal having a significantly higher strength than the cell 2, it is indicated that the interference source is located closer to the cell 1.

The positioning method described in this embodiment may be applied in a similar manner to the interfered cluster in the target area, and the first interfered cluster is only used for convenience of description. First, the grid area where the interference source may be present is determined, here by screening out the grid set located in the interfered cell.

Optionally, the obtaining the euclidean distance between each grid in the grid set and the interference source based on the distance ratio vector and the interference level ratio vector of each grid in the grid set includes:

Specifically, it is assumed that there are n interfering cells in one interfering cluster, n is a positive integer, and cell1 is the most interfering cell, i.e., the interfered cell with the highest interference level.

Fig. 4 is a schematic diagram of distances from each grid to a base station to which each interfered cell belongs, and referring to fig. 4, the distances from each grid to the base station to which each interfered cell belongs may be obtained as follows:

S1=grid 1 distance from the base station to which cell1 belongs;

s2=grid 2 distance from the base station to which cell2 belongs;

s3=grid 3 distance from the base station to which cell3 belongs;

……

s (n-1) =grid n distance from the base station to which cell belongs;

sn=grid n distance from the base station to which cell belongs.

The ratio of the distance from each grid to the base station to which each interfered cell belongs to the distance from each grid to the base station to which the interfered cell with the highest interference level belongs is:

a ₁ ＝S1/S1；

a ₂ ＝S2/S1；

……

a _(n-1) ＝S(n-1)/S1。

obtaining the distance ratio of each gridThe amount is [ a ] ₁ ，a ₂ ，a ₃ ，a ₄ ....a _(n-1) ]Within the interfered cluster, the distance ratio vectors of all grids form a distance ratio matrix:

the ratio of the interference level of the interfered cell where each grid is located to the interference level of the interfered cell with the highest interference level is:

r ₁ ＝cell1 IOT/cell1 IOT；

r ₂ ＝cell2 IOT/cell1 IOT；

……

r _(n-1) ＝cell(n-1)IOT/cell1 IOT。

where IOT (Interference over Thermal, thermal noise disturbance) represents the level of disturbance. Obtaining interference level ratio vector of each grid as r ₁ ,r ₂ ....r _(n-1) ]。

Optionally, the obtaining the euclidean distance between each grid and the interference source based on the distance ratio vector and the interference level ratio vector of each grid includes:

Specifically, according to the distance ratio vector and the interference level ratio vector of each grid, the similarity between each grid and the grid where the interference source is located is calculated, and the higher the similarity is, the greater the possibility that the interference source is present in the grid is. The similarity can be obtained by calculating the Euclidean distance between each grid and the grid where the interference source is located, and the shorter the Euclidean distance is, the higher the similarity is. For example, grid 1 and interference source EuropeDistance d ₁ The method comprises the following steps:

according to the method for positioning the uplink frequency band interference source, the determined grid where the interference source is located can be output by adopting the interference positioning algorithm, the range of uplink interference checking is reduced to the range of the grid where the interference source is finally determined, and the efficiency of interference checking is improved.

Optionally, the dividing the target area into a plurality of grids having a predetermined area includes:

Specifically, the grid cells are generally divided by square areas, but may be used to represent other shapes, and the square areas may take 50 meters in length.

According to the method for positioning the uplink frequency band interference source, disclosed by the embodiment of the application, the interference source can be positioned within the accuracy range of 50 meters by analyzing the industrial parameter data and the uplink interference statistical performance KPI data of the base station and adopting the interference positioning algorithm, so that the suspected interference source position can be rapidly identified, the uplink interference checking range can be reduced, and the interference checking efficiency can be improved.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in fig. 5, where the electronic device includes a memory 520, a transceiver 500, and a processor 510, where:

a memory 520 for storing a computer program; a transceiver 500 for transceiving data under the control of the processor 510; a processor 510 for reading the computer program in the memory 520 and performing the following operations:

Specifically, the transceiver 500 is used to receive and transmit data under the control of the processor 510.

Where in FIG. 5, a bus architecture may comprise any number of interconnected buses and bridges, with various circuits of the one or more processors, as represented by processor 510, and the memory, as represented by memory 520, being linked together. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., which are well known in the art and, therefore, will not be described further herein. The bus interface provides an interface. Transceiver 500 may be a number of elements, including a transmitter and a receiver, providing a means for communicating with various other apparatus over a transmission medium, including wireless channels, wired channels, optical cables, etc. The processor 510 is responsible for managing the bus architecture and general processing, and the memory 520 may store data used by the processor 510 in performing operations.

The processor 510 may be a central processing unit (Central Processing Unit, CPU), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a Field programmable gate array (Field-Programmable Gate Array, FPGA), or a complex programmable logic device (Complex Programmable Logic Device, CPLD), or may employ a multi-core architecture.

dividing the target area into a plurality of grids having a predetermined area;

It should be noted that, in the electronic device provided in this embodiment of the present application, all the method steps implemented by the method embodiment in which the execution body is an electronic device can be implemented, and the same technical effects can be achieved, and detailed descriptions of the same parts and beneficial effects as those of the method embodiment in this embodiment are omitted.

The embodiment of the application provides a method and a device for positioning an uplink frequency band interference source, which are used for solving the defects of higher labor cost and time cost and lower accuracy required by positioning the interference source which causes interference to an uplink frequency band in the prior art and realizing high-efficiency and accurate positioning of the uplink frequency band interference source. The method and the device are based on the same application, and because the principles of solving the problems by the method and the device are similar, the implementation of the device and the method can be referred to each other, and the repetition is not repeated.

Fig. 6 is a schematic structural diagram of an apparatus for locating an uplink frequency band interference source according to an embodiment of the present application, and referring to fig. 6, the apparatus for locating an uplink frequency band interference source according to an embodiment of the present application includes:

an interference cell clustering unit 610, configured to obtain an interfered cluster by clustering the interfered cells based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance indicator;

And the interference source positioning unit 620 is configured to determine, based on the interfered cluster, a location of an interference source in the target area.

It should be noted that, in the embodiment of the present application, the division of the units is schematic, which is merely a logic function division, and other division manners may be implemented in actual practice. In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a processor-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Optionally, according to an embodiment of the present application, the device for locating an uplink frequency band interference source, the obtaining the interfered cluster by clustering the interfered cells based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance indicator includes:

dividing the target area into a plurality of grids having a predetermined area;

Optionally, the apparatus for locating an uplink frequency band interference source according to an embodiment of the present application, wherein determining, based on the uplink interference statistical performance KPI data, the interfered cell from each cell in the target area includes:

Optionally, the device for locating an uplink frequency band interference source according to an embodiment of the present application, the determining, based on the area of the grid and the parameter data of the base station, the number of grids that can be covered by the interference source includes:

Optionally, the device for locating an uplink frequency band interference source according to an embodiment of the present application, the dividing the target area into a plurality of grids with predetermined areas includes:

Optionally, the device for locating an uplink frequency band interference source according to an embodiment of the present application, where determining, based on the interfered cluster, a location of the interference source in the target area includes:

Optionally, according to an embodiment of the present application, the device for locating an uplink frequency band interference source, the obtaining, based on a distance ratio vector and an interference level ratio vector of each grid in the grid set, a euclidean distance between each grid in the grid set and the interference source includes:

Optionally, according to an embodiment of the present application, the device for locating an uplink frequency band interference source, the obtaining, based on the distance ratio vector and the interference level ratio vector of each grid, the euclidean distance between each grid and the interference source includes:

It should be noted that, the above device provided in the embodiment of the present application can implement all the method steps implemented in the method embodiment and achieve the same technical effects, and detailed descriptions of the same parts and beneficial effects as those in the method embodiment in this embodiment are omitted.

In another aspect, an embodiment of the present application further provides a processor readable storage medium, where a computer program is stored, where the computer program is configured to cause the processor to perform the method provided in the foregoing embodiments, where the method includes:

The processor-readable storage medium may be any available medium or data storage device that can be accessed by a processor, including, but not limited to, magnetic storage (e.g., floppy disks, hard disks, magnetic tape, magneto-optical disks (MOs), etc.), optical storage (e.g., CD, DVD, BD, HVD, etc.), semiconductor storage (e.g., ROM, EPROM, EEPROM, nonvolatile storage (NAND FLASH), solid State Disk (SSD)), and the like.

Optionally, according to the processor readable storage medium of one embodiment of the present application, the obtaining the interfered cluster by clustering the interfered cells based on the parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance indicator includes:

Dividing the target area into a plurality of grids having a predetermined area;

Optionally, the determining the number of grids that can be covered by the interference source based on the area of the grids and the industrial parameter data of the base station includes:

Optionally, the clustering the interfered cells using a K-means++ clustering algorithm according to one embodiment of the present application includes:

Optionally, according to the processor readable storage medium of one embodiment of the present application, the obtaining the euclidean distance between each grid in the grid set and the interference source based on the distance ratio vector and the interference level ratio vector of each grid in the grid set includes:

Optionally, according to an embodiment of the present application, the obtaining the euclidean distance between each grid and the interference source based on the distance ratio vector and the interference level ratio vector of each grid includes:

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These processor-executable instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. A method for locating an uplink frequency band interference source, comprising:

2. The method for locating an uplink frequency band interference source according to claim 1, wherein the obtaining the interfered cluster by clustering the interfered cells based on the industrial parameter data of the base station in the target area and the KPI data of the uplink interference statistical performance key performance indicator includes:

Dividing the target area into a plurality of grids having a predetermined area;

3. The method for locating an uplink band interferer of claim 2, wherein said determining the interfered cells from each cell of the target region based on the uplink interference statistical performance KPI data comprises:

4. The method for locating an uplink band interference source according to claim 2, wherein the determining the number of grids that an interference source can cover based on the area of the grids and the reference data of the base station comprises:

5. The method for locating an uplink band interferer of claim 2, wherein said clustering the interfered cells using a K-means++ clustering algorithm comprises:

6. The method of locating an uplink band interferer of claim 2, wherein said dividing said target area into a plurality of grids having predetermined areas comprises:

7. The method for locating an uplink band interferer of claim 2, wherein said determining, based on said interfered clusters, where an interferer is located in said target area comprises:

8. The method for locating an uplink band interference source according to claim 7, wherein the obtaining the euclidean distance between each grid in the grid set and the interference source based on the distance ratio vector and the interference level ratio vector of each grid in the grid set comprises:

9. The method for locating an uplink band interferer of claim 8, wherein said deriving euclidean distances of said respective grids from said interferer based on distance ratio vectors and interference level ratio vectors of said respective grids comprises:

10. An electronic device includes a memory, a transceiver, and a processor;

the memory is used for storing a computer program; the transceiver is used for receiving and transmitting data under the control of the processor; wherein the processor is configured to read the computer program in the memory and perform the following operations:

11. The electronic device of claim 10, wherein the obtaining the interfered cluster by clustering the interfered cells based on the industrial parameter data and the uplink interference statistical performance key performance indicator KPI data of the base station in the target area comprises:

dividing the target area into a plurality of grids having a predetermined area;

12. The electronic device of claim 11, wherein the determining the interfered cell from the respective cells of the target region based on the uplink interference statistical performance KPI data comprises:

13. The electronic device of claim 11, wherein the determining the number of grids that an interfering source can cover based on the area of the grids and the parametric data of the base station comprises:

14. The electronic device of claim 11, wherein the clustering the interfered cells using a K-means++ clustering algorithm comprises:

15. The electronic device of claim 11, wherein the dividing the target region into a plurality of grids having a predetermined area comprises:

16. The electronic device of claim 11, wherein the determining, based on the interfered cluster, a location in the target region where an interference source is located comprises:

17. The electronic device of claim 16, wherein the deriving the euclidean distance of each grid in the set of grids from the interferer based on the distance ratio vector and the interference level ratio vector for each grid in the set of grids comprises:

18. The electronic device of claim 16, wherein the deriving the euclidean distance of the respective grid from the interferer based on the distance ratio vector and the interference level ratio vector of the respective grid comprises:

19. An apparatus for locating an uplink frequency band interference source, comprising:

20. A processor-readable storage medium, characterized in that the processor-readable storage medium stores a computer program for causing the processor to perform the method of locating an uplink band interference source according to any one of claims 1 to 9.