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CN-122002259-A - Intelligent identification method, system and medium for different-frequency co-station coverage cell

CN122002259ACN 122002259 ACN122002259 ACN 122002259ACN-122002259-A

Abstract

The application relates to the field of communication data, in particular to an intelligent identification method, system and medium for different-frequency co-sited coverage cells. A method for intelligently identifying different-frequency co-station coverage cells is characterized by comprising the following steps of S1, obtaining network engineering parameter data, S2, preprocessing the engineering parameter data, S3, defining at least two matching rule sets with different priorities, wherein each matching rule set comprises one or more matching conditions, the matching conditions are selected from the group consisting of identical physical site names, identical cell tail numbers, identical cell tail number module 3 values, identical longitude and latitude, the distance between the longitude and the latitude is within a preset threshold, the azimuth is identical, the difference between the azimuth is within the preset threshold, and the target cell name comprises the physical site name of a master station, so that the problems of low efficiency, poor accuracy and weak adaptability of the prior art can be solved.

Inventors

  • LI YANJUN
  • LIU MEIJUN
  • Dai Shangxin
  • FENG YUN
  • HE YI

Assignees

  • 重庆信科通信工程有限公司

Dates

Publication Date
20260508
Application Date
20260120

Claims (8)

  1. 1. An intelligent recognition method for different-frequency co-station coverage cells is characterized by comprising the following steps: s1, acquiring network engineering parameter data, wherein the data at least comprises a base station identifier, an existing network base station name, a cell name, longitude and latitude and an azimuth angle; s2, preprocessing the engineering parameter data, wherein the preprocessing comprises the following steps: s21, generating a physical site name by removing tail numbers and/or letters based on the name of the current network base station; S22, extracting a first continuous number sequence from right to left based on the cell name to generate a cell tail number; Defining at least two matching rule groups with different priorities, wherein the high-priority rule group is executed before the low-priority rule group, each matching rule group comprises one or more matching conditions, and the matching conditions are selected from the group consisting of identical physical site names, identical cell tail numbers, identical cell tail number module 3 values, identical longitude and latitude, the distance between the longitude and the latitude being in a preset threshold, the azimuth being identical, the azimuth difference being in the preset threshold, and the target cell name comprising the physical site name of the master station; For the matching rule group executed at present, if a pair of cells meet all matching conditions of the rule group, marking the pair of cells as a co-sited coverage cell pair, and removing the matched cells from a set to be matched; and S5, outputting all marked co-sited coverage cell pairs.
  2. 2. The method according to claim 1, wherein in step S3, the high priority rule set includes three matching conditions of "same physical site name", "same cell tail number", and "difference in azimuth within a first preset threshold".
  3. 3. The method of claim 2, wherein the first predetermined threshold value ranges from 5 degrees to 15 degrees.
  4. 4. The method according to claim 1, wherein in step S3, the low priority rule set includes three matching conditions of "physical station name is the same", "azimuth difference is within a second preset threshold", and "distance between longitude and latitude is within a third preset threshold", wherein the second preset threshold is greater than the first preset threshold.
  5. 5. The method of claim 4, wherein the second preset threshold value ranges from 20 degrees to 40 degrees and the third preset threshold value ranges from 30 meters to 100 meters.
  6. 6. The method of claim 1, further comprising defining a set of matching rules for identifying remote cells having a lower priority than said set of high priority rules, the set of rules comprising two matching conditions of "target cell name includes primary station physical site name" and "difference in azimuth is within a preset threshold".
  7. 7. An intelligent identification system for a different frequency co-sited coverage cell adapted for use in the method of any one of claims 1-6, comprising: The data acquisition and preprocessing module is used for acquiring engineering parameter data and executing the preprocessing step; a rule configuration module for receiving user input to define the at least two matching rule sets having different priorities; The core analysis engine is used for executing the matching rule group according to the priority order and carrying out matching mark and set updating; And the result output module is used for outputting the final co-sited coverage cell pair.
  8. 8. Computer readable storage medium, characterized in that the computer storage medium stores a computer program which, when executed by a processor, implements the method according to any of claims 1-6.

Description

Intelligent identification method, system and medium for different-frequency co-station coverage cell Technical Field The application relates to the field of communication data, in particular to an intelligent identification method, system and medium for different-frequency co-sited coverage cells. Background In a mobile communication network, particularly in the context of the collaborative development of a 4G/5G multi-layer network, there are a large number of cells (i.e. "inter-frequency co-sited coverage cells") in the network that are constructed co-sited, but operate in different frequency bands. The cell pairs are accurately and efficiently identified, and the method is a key basic work for accurately planning a network, optimizing load balance, improving switching success rate and realizing multi-layer network coordination. Currently, the identification of such cell pairs within the industry relies primarily on human experience or simple scripting tools. The manual mode needs engineers to compare the information such as site names, longitude and latitude, azimuth angles and the like in the engineering parameter table, the efficiency is extremely low, and inconsistent results are easily caused by personnel experience differences. The existing scripting tool usually adopts a single and rigid matching rule (for example, only judging whether the site names are completely the same or whether the longitudes and latitudes are absolutely consistent), and is difficult to cope with the actual situation that the actual network engineering parameters are complex and changeable, and the main appearance is that: naming non-normative, in engineering parameters of different provinces and cities and different periods, naming rules of site names and cell names are not uniform, for example, the same physical site may be named as XX building 1 and XX building A, and a method based on accurate name matching is invalid. The data has errors, namely unavoidable measurement or recording errors exist in the data such as longitude and latitude, azimuth and the like in engineering parameters, the fault tolerance is poor based on the matching rules with absolute equality, and a large number of missed matches are easy to generate. Complex scenes cannot be identified, and for complex scenes such as remote cells (the cell names of which may contain the primary station names but differ in geographic location), simple rules cannot be effectively identified. The matching confidence cannot be distinguished, that is, the reliability of the matching result cannot be graded by the existing method, and all the results are mixed together, so that the priority ordering of the subsequent optimization work is not facilitated. Therefore, there is a strong need in the art for an automated solution that can adaptively process non-canonical data, tolerate parameter errors, and simulate expert complex decision logic, to overcome the deficiencies of the prior art. Disclosure of Invention In order to solve the problems of low efficiency, poor accuracy and weak adaptability in the prior art. The application provides an intelligent identification method, system and medium for different-frequency co-station coverage cells. In a first aspect, the present application provides an intelligent identification method for different frequency co-station coverage cells, which adopts the following technical scheme: An intelligent recognition method for different frequency co-station coverage cells comprises the following steps: s1, acquiring network engineering parameter data, wherein the data at least comprises a base station identifier, an existing network base station name, a cell name, longitude and latitude and an azimuth angle; s2, preprocessing the engineering parameter data, wherein the preprocessing comprises the following steps: s21, generating a physical site name by removing tail numbers and/or letters based on the name of the current network base station; S22, extracting a first continuous number sequence from right to left based on the cell name to generate a cell tail number; Defining at least two matching rule groups with different priorities, wherein the high-priority rule group is executed before the low-priority rule group, each matching rule group comprises one or more matching conditions, and the matching conditions are selected from the group consisting of identical physical site names, identical cell tail numbers, identical cell tail number module 3 values, identical longitude and latitude, the distance between the longitude and the latitude being in a preset threshold, the azimuth being identical, the azimuth difference being in the preset threshold, and the target cell name comprising the physical site name of the master station; For the matching rule group executed at present, if a pair of cells meet all matching conditions of the rule group, marking the pair of cells as a co-sited coverage cell pair, and removing the matched cells from