CN117729560A - Method and device for determining antenna parameters - Google Patents

Method and device for determining antenna parameters Download PDF

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Publication number
CN117729560A
CN117729560A CN202211137608.XA CN202211137608A CN117729560A CN 117729560 A CN117729560 A CN 117729560A CN 202211137608 A CN202211137608 A CN 202211137608A CN 117729560 A CN117729560 A CN 117729560A
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China
Prior art keywords
cell
terminal
iteration
antenna
determining
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CN202211137608.XA
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Chinese (zh)
Inventor
王郭燕
李建国
周先文
张劲超
庞磊
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ZTE Corp
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ZTE Corp
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Priority to CN202211137608.XA priority Critical patent/CN117729560A/en
Priority to PCT/CN2023/117284 priority patent/WO2024061001A1/en
Publication of CN117729560A publication Critical patent/CN117729560A/en
Pending legal-status Critical Current

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The application provides a method and a device for determining antenna parameters, which relate to the field of mobile communication and can set more accurate parameters such as an antenna mechanical angle for a cell with lower cost. The method comprises the following steps: acquiring a set of cells to be optimized, an antenna parameter alternative set corresponding to each cell in the set and measurement information of each terminal in a plurality of terminals, and determining a target antenna parameter of each cell according to the antenna parameter alternative set and the measurement information of each terminal. The antenna parameter alternative set corresponding to any cell comprises a plurality of alternative antenna parameters, and any alternative antenna parameter comprises an antenna mechanical angle of the cell. The plurality of terminals reside in cells in the set, and the measurement information of any one terminal includes a signal quality of each cell measured by the terminal and an arrival direction angle of the terminal with respect to each cell.

Description

Method and device for determining antenna parameters
Technical Field
The present invention relates to the field of mobile communications, and in particular, to a method and apparatus for determining antenna parameters.
Background
In a communication system, each network device corresponds to a coverage area and provides wireless access service for terminals within the coverage area. The coverage area of the network device may be divided into a plurality of areas, for example, into a plurality of cells (cells), where coverage areas of different cells are different, and a terminal located in a certain cell may access the network device through the cell. If the coverage area of the cell is unreasonable, the terminals in the cell are intensively distributed at the edge of the cell, so that the signal quality of the terminals is reduced, and the user experience is affected. Therefore, how to optimize the coverage of a cell to improve the signal quality of terminals within the cell has been a hotspot under investigation.
At present, engineers mainly optimize the coverage of a cell through site survey and empirically adjusting relevant parameters of the cell, so that a great deal of manpower and material resources are consumed, and the optimization result is not ideal.
Disclosure of Invention
The application provides a method and a device for determining antenna parameters, which can set more accurate parameters such as antenna mechanical angles and the like for a cell with lower cost.
In order to achieve the above purpose, the present application adopts the following technical scheme:
in a first aspect, the present application provides a method for determining an antenna parameter, the method including: acquiring a set of cells to be optimized; acquiring an antenna parameter alternative set corresponding to each cell in the set, wherein the antenna parameter alternative set corresponding to any cell comprises a plurality of alternative antenna parameters, and any one of the alternative antenna parameters comprises an antenna mechanical angle of the cell; acquiring measurement information of each terminal in a plurality of terminals, wherein the plurality of terminals reside in cells in a set, and the measurement information of any one terminal comprises signal quality of each cell measured by the terminal and an arrival direction angle of the terminal relative to each cell; and determining the target antenna parameters of each cell according to the plurality of antenna parameters and the measurement information of each terminal.
Based on the technical scheme, the target antenna parameters can be determined for each cell in the set of cells to be optimized, so that large manpower and material resources are not required, and the determined target antenna parameters are reasonable because the signal quality of each cell and the arrival direction angle of the terminal relative to each cell, which are measured by the terminal in each cell in the set, are considered when the target antenna parameters are determined. In this way, after optimizing the corresponding cell according to the target antenna parameter, the signal quality of the terminal in the cell can be improved.
In one possible implementation, determining the target antenna parameter of each cell according to the antenna parameter candidate set and the measurement information of each terminal includes: determining a plurality of iteration parameters in the antenna parameter alternative set by adopting an ant colony algorithm, and determining pheromone corresponding to each iteration parameter according to the measurement information of each terminal; and determining the target antenna parameters of each cell according to the pheromone corresponding to each iteration parameter.
In one possible implementation manner, determining the pheromone corresponding to each iteration parameter according to the measurement information of each terminal includes: according to the measurement information of each terminal, under the condition that the cells in the set are configured as corresponding iteration parameters, the signal quality estimated value and the signal-to-interference-and-noise ratio of each terminal are determined; and determining the pheromone corresponding to each iteration parameter according to the signal quality estimated value and the signal-to-interference-and-noise ratio of each terminal.
In one possible implementation manner, in a case that it is determined that cells in the set are configured as corresponding iteration parameters according to measurement information of each terminal, a signal quality estimation value and a signal-to-interference-and-noise ratio of each terminal include: determining a signal quality estimated value of each terminal under the condition that a plurality of cells are configured as corresponding iteration parameters according to the measurement information of each terminal; and determining the signal-to-interference-and-noise ratio of each terminal under the condition that the cells in the set are configured as corresponding iteration parameters according to the signal quality estimated value of each terminal in the plurality of terminals.
In one possible implementation manner, in a case that it is determined that cells in the set are configured as corresponding iteration parameters according to measurement information of each terminal, the signal quality estimation value of each terminal includes: according to the corresponding arrival direction angle of each terminal relative to each cell, determining an arrival direction angle estimated value of each terminal under the condition that the cells in the set are configured as corresponding iteration parameters; and determining the signal quality estimated value of each terminal according to the arrival direction angle estimated value of each terminal and the signal quality of each cell measured by each terminal.
In one possible implementation manner, determining the pheromone corresponding to each iteration parameter according to the signal quality estimated value and the signal-to-interference-and-noise ratio of each terminal includes: determining a signal quality distribution function corresponding to each iteration parameter according to the signal quality estimation value of each terminal, wherein the signal quality distribution function corresponding to any one iteration parameter is used for indicating the signal quality condition of a plurality of terminals under the condition that cells in a set are configured as iteration parameters; according to the signal-to-interference-and-noise ratio of each terminal, determining a signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter, wherein the signal-to-interference-and-noise ratio distribution function corresponding to any one iteration parameter is used for indicating the signal-to-interference-and-noise ratio conditions of a plurality of terminals under the condition that cells in a set are configured as iteration parameters; and determining the pheromone corresponding to each iteration parameter according to the signal quality distribution function corresponding to each iteration parameter and the signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter.
In one possible implementation manner, for any one first iteration parameter of the multiple iteration parameters, determining an pheromone corresponding to the first iteration parameter according to a signal quality distribution function corresponding to the first iteration parameter and a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter includes: acquiring first signal quality, wherein the first signal quality is the input value of a signal quality distribution function corresponding to a first iteration parameter under the condition that the output value of the signal quality distribution function corresponding to the first iteration parameter is a first numerical value; acquiring a first signal-to-interference-and-noise ratio, wherein the first signal-to-interference-and-noise ratio is an input value of a signal-to-interference-and-noise ratio distribution function corresponding to a first iteration parameter under the condition that the first signal-to-interference-and-noise ratio is a second value of an output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter; and determining the pheromone corresponding to the first iteration parameter according to the first signal quality and the first signal-to-interference-and-noise ratio.
In one possible implementation manner, determining the pheromone corresponding to the first iteration parameter according to the first signal quality and the first signal-to-interference-and-noise ratio includes: acquiring second signal quality, wherein the second signal quality is the input value of the signal quality distribution function corresponding to the first iteration parameter under the condition that the output value of the signal quality distribution function corresponding to the first iteration parameter is a third numerical value; acquiring a second signal-to-interference-and-noise ratio, wherein the second signal-to-interference-and-noise ratio is an input value of a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter under the condition that the second signal-to-interference-and-noise ratio is a fourth value of an output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter; and determining the pheromone corresponding to the first iteration parameter according to the first signal quality, the first signal-to-interference-and-noise ratio, the second signal quality and the second signal-to-interference-and-noise ratio.
In one possible implementation, the antenna mechanical angle of the cell includes an antenna mechanical azimuth angle of the cell and an antenna mechanical downtilt angle of the cell.
In one possible implementation, any one of the alternative antenna parameters further includes digital weight information corresponding to the cell.
In one possible implementation, the method further includes: acquiring a plurality of pieces of alternative digital weight information corresponding to each cell in the set; determining a plurality of iteration information in a plurality of alternative digital weight information by adopting an ant colony algorithm, and determining pheromone corresponding to each iteration information according to the measurement information of each terminal; and determining the target digital weight information of each cell according to the pheromone corresponding to each piece of iteration information.
In one possible implementation, obtaining the set of cells to be optimized includes: acquiring a first cell, wherein the duty ratio of a terminal in the weak coverage area of the first cell is larger than or equal to a preset threshold value; the first cell and a second cell are classified into a set of cells to be optimized, wherein the second cell comprises a cell co-sited with the first cell and/or a cell adjacent to the first cell.
In one possible implementation, acquiring the first cell includes: acquiring N pieces of digital weight information corresponding to a third cell, wherein N is an integer greater than 1; acquiring N antenna gains corresponding to the N digital weight information according to the N digital weight information; acquiring the weak coverage area of a third cell according to the N antenna gains; and if the duty ratio of the terminal in the weak coverage area of the third cell is greater than or equal to a preset threshold value, determining the third cell as the first cell.
In one possible implementation, obtaining the weak coverage of the third cell according to the N antenna gains includes: according to the N antenna gains, N horizontal coverage areas and N vertical coverage areas corresponding to the N digital weight information are determined; and determining the weak coverage of the third cell according to the N horizontal coverage areas and the N vertical coverage areas.
In one possible implementation, any one of the horizontal coverage areas is greater than or equal to a first azimuth angle and less than or equal to a second azimuth angle; determining the weak coverage of the third cell according to the N horizontal coverage areas and the N vertical coverage areas, including: the minimum azimuth is determined among the N first azimuths, the maximum azimuth is determined among the N second azimuths, and the weak coverage of the third cell is less than or equal to the minimum azimuth and greater than or equal to the maximum azimuth.
In one possible implementation, any one of the vertical coverage ranges is greater than or equal to the first downtilt angle and less than or equal to the second downtilt angle; determining the weak coverage of the third cell according to the N horizontal coverage ranges and the N vertical coverage ranges, further comprising: the minimum downtilt is determined among the N first downtilt angles, the maximum downtilt is determined among the N second downtilt angles, and the weak coverage of the third cell is less than or equal to the minimum downtilt angle and greater than or equal to the maximum downtilt angle.
In a second aspect, the present application provides an apparatus for determining an antenna parameter, the apparatus comprising: the device comprises an acquisition module and a processing module; the acquisition module is used for acquiring a set of cells to be optimized; the acquisition module is further used for acquiring an antenna parameter alternative set corresponding to each cell in the set, wherein the antenna parameter alternative set corresponding to any cell comprises an antenna mechanical angle of the cell; the acquisition module is further configured to acquire measurement information of each of a plurality of terminals, where the plurality of terminals reside in cells in a set, and the measurement information of any one terminal includes signal quality of each cell measured by the terminal and an arrival direction angle of the terminal relative to each cell; the processing module is used for determining the target antenna parameters of each cell according to the antenna parameter alternative set and the measurement information of each terminal.
In a possible implementation manner, the processing module is specifically configured to determine a plurality of iteration parameters in the antenna parameter alternative set by adopting an ant colony algorithm, and determine an pheromone corresponding to each iteration parameter according to measurement information of each terminal; the processing module is further specifically configured to determine a target antenna parameter of each cell according to the pheromone corresponding to each iteration parameter.
In a possible implementation manner, the processing module is further specifically configured to determine, according to measurement information of each terminal, a signal quality estimated value and a signal-to-interference-and-noise ratio of each terminal in a case that cells in the set are configured as corresponding iteration parameters; the processing module is further specifically configured to determine, according to the signal quality estimated value and the signal-to-interference-and-noise ratio of each terminal, a pheromone corresponding to each iteration parameter.
In a possible implementation manner, the processing module is further specifically configured to determine, according to measurement information of each terminal, a signal quality estimated value of each terminal in a case where the plurality of cells are configured as corresponding iteration parameters; the processing module is further specifically configured to determine, according to the signal quality estimated value of each of the plurality of terminals, a signal-to-interference-and-noise ratio of each terminal in a case where the cells in the set are configured as corresponding iteration parameters.
In a possible implementation manner, the processing module is further specifically configured to determine, according to a corresponding direction of arrival angle of each terminal with respect to each cell, an estimated value of the direction of arrival angle of each terminal in a case where cells in the set are configured as corresponding iteration parameters; the processing module is further specifically configured to determine a signal quality estimation value of each terminal according to the estimated value of the arrival direction angle of each terminal and the signal quality of each cell measured by each terminal.
In a possible implementation manner, the processing module is further specifically configured to determine, according to the signal quality estimated value of each terminal, a signal quality distribution function corresponding to each iteration parameter, where any one iteration parameter corresponds to the signal quality distribution function and is used to indicate signal quality conditions of a plurality of terminals when a cell in the set is configured as an iteration parameter; the processing module is further specifically configured to determine, according to a signal-to-interference-and-noise ratio of each terminal, a signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter, where the signal-to-interference-and-noise ratio distribution function corresponding to any one iteration parameter is used to indicate a signal-to-interference-and-noise ratio condition of a plurality of terminals under a condition that a cell in a set is configured as an iteration parameter; the processing module is further specifically configured to determine an pheromone corresponding to each iteration parameter according to the signal quality distribution function corresponding to each iteration parameter and the signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter.
In one possible implementation manner, for any one first iteration parameter of the multiple iteration parameters, the processing module is further specifically configured to obtain a first signal quality, where the first signal quality is an input value of a signal quality distribution function corresponding to the first iteration parameter when an output value of the signal quality distribution function corresponding to the first iteration parameter is a first numerical value; the processing module is further specifically configured to obtain a first signal-to-interference-and-noise ratio, where the first signal-to-interference-and-noise ratio is an input value of a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter when the output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter is a second value; the processing module is further specifically configured to determine, according to the first signal quality and the first signal-to-interference-and-noise ratio, an pheromone corresponding to the first iteration parameter.
In a possible implementation manner, the processing module is further specifically configured to obtain a second signal quality, where the second signal quality is an input value of a signal quality distribution function corresponding to the first iteration parameter when an output value of the signal quality distribution function corresponding to the first iteration parameter is a third value; the processing module is further specifically configured to obtain a second signal-to-interference-and-noise ratio, where the second signal-to-interference-and-noise ratio is an input value of a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter when the output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter is a fourth value; the processing module is further specifically configured to determine an pheromone corresponding to the first iteration parameter according to the first signal quality, the first signal-to-interference-and-noise ratio, the second signal quality and the second signal-to-interference-and-noise ratio.
In one possible implementation, the antenna mechanical angle of the cell includes an antenna mechanical azimuth angle of the cell and an antenna mechanical downtilt angle of the cell.
In one possible implementation, any one of the alternative antenna parameters further includes digital weight information corresponding to the cell.
In a possible implementation manner, the obtaining module is further configured to obtain a plurality of candidate digital weight information corresponding to each cell in the set; the processing module is also used for determining a plurality of iteration information in a plurality of alternative digital weight information by adopting an ant colony algorithm, and determining pheromones corresponding to each iteration information according to the measurement information of each terminal; the processing module is further used for determining the target digital weight information of each cell according to the pheromone corresponding to each piece of iteration information.
In one possible implementation manner, the acquiring module is specifically configured to acquire a first cell, where a duty ratio of a terminal in a weak coverage area of the first cell is greater than or equal to a preset threshold; the acquisition module is further specifically configured to assign the first cell and the second cell to a set of cells to be optimized, where the second cell includes a cell co-sited with the first cell and/or a cell adjacent to the first cell.
In a possible implementation manner, the obtaining module is further specifically configured to obtain N digital weight information corresponding to the third cell, where N is an integer greater than 1; the acquisition module is also specifically used for acquiring N antenna gains corresponding to the N digital weight information according to the N digital weight information; the acquisition module is further specifically configured to acquire a weak coverage area of the third cell according to the N antenna gains; the acquiring module is further specifically configured to determine that the third cell is the first cell if the duty ratio of the terminal in the weak coverage area of the third cell is greater than or equal to a preset threshold.
In one possible implementation manner, the processing module is specifically configured to determine, according to N antenna gains, N horizontal coverage ranges and N vertical coverage ranges corresponding to N digital weight information; the processing module is further specifically configured to determine a weak coverage area of the third cell according to the N horizontal coverage areas and the N vertical coverage areas.
In one possible implementation, any one of the horizontal coverage areas is greater than or equal to a first azimuth angle and less than or equal to a second azimuth angle; the processing module is further specifically configured to determine a smallest azimuth angle among the N first azimuth angles, determine a largest azimuth angle among the N second azimuth angles, and the weak coverage area of the third cell is smaller than or equal to the smallest azimuth angle and is greater than or equal to the largest azimuth angle.
In one possible implementation, any one of the vertical coverage ranges is greater than or equal to the first downtilt angle and less than or equal to the second downtilt angle; the processing module is further specifically configured to determine a minimum downtilt angle from the N first downtilt angles, determine a maximum downtilt angle from the N second downtilt angles, and the weak coverage area of the third cell is smaller than or equal to the minimum downtilt angle and is greater than or equal to the maximum downtilt angle.
In a third aspect, the present application provides an apparatus for determining an antenna parameter, the apparatus comprising: a processor and a communication interface; the communication interface is coupled to a processor for running a computer program or instructions to implement the method of determining antenna parameters as described in the first aspect and any one of the possible implementations of the first aspect.
In a fourth aspect, the present application provides a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform a method of determining antenna parameters as described in any one of the possible implementations of the first aspect and the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of determining antenna parameters as described in any one of the possible implementations of the first aspect and the first aspect.
In a sixth aspect, embodiments of the present application provide a chip comprising a processor and a communication interface, the communication interface and the processor being coupled, the processor being configured to execute a computer program or instructions to implement the method of determining antenna parameters as described in any one of the possible implementations of the first aspect and the first aspect.
Specifically, the chip provided in the embodiments of the present application further includes a memory, configured to store a computer program or instructions.
The technical effects caused by any one of the possible implementation manners of the second aspect to the sixth aspect may be referred to the technical effects caused by the foregoing first aspect and the different possible implementation manners of the first aspect, which are not described herein.
Drawings
Fig. 1 is a schematic architecture diagram of a communication system according to an embodiment of the present application;
fig. 2 is a flowchart of a method for determining antenna parameters according to an embodiment of the present application;
fig. 3 is a flowchart of another method for determining antenna parameters according to an embodiment of the present application;
fig. 4 is a flowchart of another method for determining antenna parameters according to an embodiment of the present application;
fig. 5 is a flowchart of a method for acquiring a cell to be optimized according to an embodiment of the present application;
FIG. 6 is a schematic view of a horizontal angle provided by an embodiment of the present application;
fig. 7 is an antenna gain diagram provided in an embodiment of the present application;
fig. 8 is a schematic structural diagram of a device for determining antenna parameters according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of another device for determining antenna parameters according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a chip according to an embodiment of the present application.
Detailed Description
The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone.
The terms "first" and "second" and the like in the description and in the drawings are used for distinguishing between different objects or for distinguishing between different processes of the same object and not for describing a particular sequential order of objects.
Furthermore, references to the terms "comprising" and "having" and any variations thereof in the description of the present application are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or apparatus.
It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In the description of the present application, unless otherwise indicated, the meaning of "a plurality" means two or more.
The following describes embodiments of the present application in detail with reference to the accompanying drawings.
The method provided by the embodiment of the application can be applied to various communication systems. For example, the communication system may be a long term evolution (long term evolution, LTE) system, a fifth generation (5th generation,5G) communication system, a Wi-Fi system, a third generation partnership project (3rd generation partnership project,3GPP) related communication system, a future evolution communication system (e.g., sixth generation (6th generation,6G) communication system, etc.), or a system incorporating multiple systems, without limitation. The method provided in the embodiment of the present application will be described below by taking the communication system 10 shown in fig. 1 as an example. Fig. 1 is only a schematic diagram, and does not constitute a limitation on the applicable scenario of the technical solution provided in the present application.
Fig. 1 is a schematic diagram of a communication system 10 according to an embodiment of the present application. In fig. 1, communication system 10 may include a network device 101, and a terminal 102 and a terminal 103 in communication with network device 101. Optionally, the communication system 10 further comprises a computing device 104 in communication with the network device 101. Optionally, the communication system 10 further comprises a network device 105 in communication with the network device 101 or the computing apparatus 104, and a terminal 106 and a terminal 107 in communication with the network device 105.
In fig. 1, a network device may provide a wireless access service for a terminal. Specifically, each network device corresponds to a service coverage area, and a terminal entering the area can communicate with the network device to receive the wireless access service provided by the network device. Alternatively, the service coverage may comprise one or more cells. For example, the service coverage area corresponding to the network device 101 includes cell 1 and cell 2, the terminal 102 accesses the network device 101 through cell 1, and the terminal 103 accesses the network device 101 through cell 2.
The network device in the embodiment of the present application, such as the network device 101 or the network device 105, may be any device having a radio transceiver function, for example, a base station in LTE, a base station in New Radio (NR), or a base station of subsequent evolution of 3 GPP.
The terminal in the embodiment of the application includes, for example: the terminal 102, the terminal 103, the terminal 106, or the terminal 107 is any device having a wireless transmitting/receiving function. For example, the terminal is a handheld device (e.g., a cell phone or tablet computer, etc.), an in-vehicle device, a wearable device, a terminal or computing device in an internet of things (internet of things, ioT) system, etc. with wireless communication functionality. A terminal may also be referred to as a terminal device, or User Equipment (UE), without limitation.
The computing device 104 in fig. 1 may be any device having communication and computing capabilities. For example, the computing device 104 is a server, computer, cloud server, or the like.
In some embodiments, the network device 101 may obtain a set of cells to be optimized. The set may include cells of the network device 101. Optionally, the set further comprises cells of the network device 105. The network device 101 may further obtain an alternative set of antenna parameters corresponding to each cell in the set and measurement information of each terminal in the plurality of terminals, and determine a target antenna parameter of each cell according to the alternative set of antenna parameters and the measurement information of each terminal. The antenna parameter alternative set corresponding to any cell comprises a plurality of alternative antenna parameters, and any alternative antenna parameter comprises an antenna mechanical angle of the cell. The plurality of terminals reside in cells in the set, and the measurement information of any one terminal includes a signal quality of each cell measured by the terminal and a direction-of-arrival (DOA) angle of the terminal with respect to each cell (may also be referred to as an angle of arrival). In this way, the network device 101 may determine the target antenna parameter for each cell in the set, which does not consume large manpower and material resources, and when determining the target antenna parameter, considers the signal quality of each cell measured by the terminal in each cell in the set and the arrival direction angle of the terminal with respect to each cell, so that the determined target antenna parameter is more reasonable. In this way, after optimizing the corresponding cell according to the target antenna parameter, the signal quality of the terminal in the cell can be improved. The above process will be specifically described in the following methods shown in fig. 2 to 4, and will not be described herein.
In other embodiments, the computing device 104 may obtain a set of cells to be optimized. The set may include cells of the network device 101. Optionally, the set further comprises cells of the network device 105. The computing device 104 may further obtain an alternative set of antenna parameters corresponding to each cell in the set and measurement information of each terminal in the plurality of terminals, and determine a target antenna parameter of each cell according to the alternative set of antenna parameters and the measurement information of each terminal. The antenna parameter alternative set corresponding to any cell comprises a plurality of alternative antenna parameters, and any alternative antenna parameter comprises an antenna mechanical angle of the cell. The plurality of terminals reside in cells in the set, and the measurement information of any one terminal includes the signal quality of each cell measured by the terminal and the arrival direction angle of the terminal with respect to each cell. In this way, the computing device 104 may determine the target antenna parameter for each cell in the set, which does not consume large manpower and material resources, and when determining the target antenna parameter, considers the signal quality of each cell measured by the terminal in each cell in the set and the arrival direction angle of the terminal relative to each cell, so that the determined target antenna parameter is reasonable. In this way, after optimizing the corresponding cell according to the target antenna parameter, the signal quality of the terminal in the cell can be improved. The above process will be specifically described in the following methods shown in fig. 2 to 4, and will not be described herein.
The communication system 10 shown in fig. 1 is for example only and is not intended to limit the scope of the present application. Those skilled in the art will appreciate that in particular implementations, communication system 10 may include other devices, and that the number of network devices, terminals, or computing devices may be determined according to particular needs without limitation.
As shown in fig. 2, a method for determining antenna parameters according to an embodiment of the present application may include the following steps:
s201: the first device obtains a set of cells to be optimized.
The first device may be the network apparatus 101 or the computing device 104 in the communication system 10 shown in fig. 1.
One possible design, the set of cells to be optimized may include a plurality of cells to be optimized. The plurality of cells to be optimized may be cells belonging to the same network device, or may be cells belonging to different network devices, without limitation.
Illustratively, taking the communication system 10 shown in fig. 1 as an example, the set of cells to be optimized includes a plurality of cells of the network device 101. Alternatively, the set of cells to be optimized comprises at least one cell of the network device 101 and at least one cell of the network device 105.
It will be appreciated that, in the case where the first apparatus is the network device 101, the specific procedure of the first apparatus for performing the method provided in the embodiment of the present application may be different from that in the case where the first apparatus is the computing apparatus 104. The details are set forth below.
Case 1: the first means is a network device 101.
In a possible implementation manner, the network device 101 obtains the set of cells to be optimized through S2011-S2012 described below. Alternatively, the network device 101 obtains a set of cells to be optimized in response to an input of a worker.
Case 2: the first device is a computing device 104.
In a possible implementation manner, the network device 101 obtains the set of cells to be optimized through S2011-S2012 described below, and sends the set of cells to be optimized to the computing device 104. Accordingly, the computing means 104 receives a set of cells to be optimized from the network device 101. Alternatively, the computing device 104 obtains a set of cells to be optimized in response to an input from a worker.
S202: the first device obtains an antenna parameter alternative set corresponding to each cell in the set.
The antenna parameter alternative set corresponding to any one of the cells to be optimized comprises a plurality of alternative antenna parameters. Any one of the alternative antenna parameters includes the antenna mechanical angle of the cell. The antenna mechanical angle is within a range of antenna mechanical angles that the cell is allowed to configure.
The antenna mechanical angle of the cell includes an antenna mechanical azimuth angle of the cell (hereinafter referred to as a mechanical azimuth angle of the cell) and an antenna mechanical downtilt angle of the cell (hereinafter referred to as a mechanical downtilt angle of the cell). The mechanical azimuth angle of the cell is the included angle between the horizontal normal direction and the north direction of the cell, and the mechanical downtilt angle of the cell is the included angle between the vertical normal direction and the horizontal plane of the cell.
The following description will be given by taking an example that the set of cells to be optimized includes cell 1 and cell 2, and the range of the mechanical azimuth angle that cell 1 allows to be configured is [ -60 °,60 ° ], the range of the mechanical azimuth angle that cell 2 allows to be configured is [60 °,180 ° ], and the mechanical downtilt angles that cell 1 and cell 2 allow to be configured are 3 °,6 ° or 9 °.
Example 1, the corresponding set of alternative antenna parameters for cell 1 includes two alternative antenna parameters, the first alternative antenna parameter including a mechanical azimuth angle 1 of cell 1 (e.g., -40 °) and a mechanical downtilt angle 1 of cell 1 (e.g., 3 °), and the second alternative antenna parameter including a mechanical azimuth angle 2 of cell 1 (e.g., 20 °) and a mechanical downtilt angle 2 of cell 1 (e.g., 6 °). The corresponding set of alternative antenna parameters for cell 2 comprises two alternative antenna parameters, the first alternative antenna parameter comprising the mechanical azimuth angle 1 (e.g. 90 °) of cell 2 and the mechanical downtilt angle 1 (e.g. 3 °) of cell 2, and the second alternative antenna parameter comprising the mechanical azimuth angle 2 (e.g. 150 °) of cell 2 and the mechanical downtilt angle 2 (e.g. 3 °) of cell 2.
It should be appreciated that example 1 above is merely an example of a cell-corresponding alternative set of antenna parameters, which may include more parameters than those shown in example 1 in a particular application. For example, the alternative set of antenna parameters corresponding to cell 1 further includes a third alternative antenna parameter and a fourth alternative antenna parameter ….
Optionally, any one of the alternative antenna parameters further includes digital weight information corresponding to the cell. The digital weight information corresponding to the cell may include an azimuth angle of the cell and/or a downtilt angle of the cell. Optionally, the digital weight information corresponding to the cell may further include a horizontal lobe width of the cell and/or a vertical lobe width of the cell.
The azimuth angle of the cell is an included angle between the main coverage direction of the digital weight information corresponding to the cell and the horizontal normal direction of the cell. The downtilt angle of a cell is the included angle between the main coverage direction of the digital weight information corresponding to the cell and the normal direction perpendicular to the cell. The horizontal lobe width of a cell and the vertical lobe width of a cell may refer to the half-power angle of the index weight information. Wherein the horizontal lobe width of the cell characterizes the horizontal coverage width of the digital weight information, such as the horizontal 3dB lobe width or the horizontal 6dB lobe width. The vertical lobe width of a cell characterizes the vertical coverage width of the digital weight information, such as the vertical 3dB lobe width or the vertical 6dB lobe width.
It will be appreciated that the azimuth of a cell is included in the azimuth range that the cell is allowed to configure and the downtilt of a cell is included in the downtilt range that the cell is allowed to configure. The horizontal lobe width of a cell is included in the range of horizontal lobe widths allowed to be configured by the cell, and the vertical lobe width of a cell is included in the range of vertical lobe widths allowed to be configured by the cell.
The following description will be given by taking an example that the set of cells to be optimized includes cell 1 and cell 2, the azimuth angle range allowed to be configured by cell 1 and cell 2 is [ -20 °,20 ° ], the downtilt angle range allowed to be configured by cell 1 and cell 2 is [0 °,15 ° ], the horizontal 3dB lobe width range allowed to be configured by cell 1 and cell 2 is [45 °,65 ° ], and the vertical 3dB lobe width allowed to be configured by cell 1 and cell 2 is 6 °.
For example 1 above, the first alternative antenna parameters for cell 1 also include azimuth angle 1 of cell 1 (e.g., -15 °) and downtilt angle 1 of cell 1 (e.g., 0 °). The second alternative antenna parameters corresponding to cell 1 also include azimuth angle 2 (e.g., 10 °) of cell 1 and downtilt angle 2 (e.g., 12 °) of cell 1. The first alternative antenna parameters corresponding to cell 2 also include azimuth angle 1 (e.g., -10 °) of cell 2 and downtilt angle 1 (e.g., 5 °) of cell 2. The second alternative antenna parameters corresponding to cell 2 also include azimuth angle 2 (e.g., 15 °) of cell 2 and downtilt angle 2 (e.g., 12 °) of cell 2. Optionally, the first alternative antenna parameters corresponding to cell 1 also include a horizontal 3dB lobe width 1 of cell 1 (e.g., 50 °) and a vertical 3dB lobe width of cell 1 (e.g., 6 °). The second alternative antenna parameters for cell 1 also include cell 1 horizontal 3dB lobe width 2 (e.g., 65 °) and cell 1 vertical 3dB lobe width (e.g., 6 °). The corresponding first alternative antenna parameters for cell 2 also include a horizontal 3dB lobe width 1 for cell 2 (e.g., 50 °) and a vertical 3dB lobe width for cell 2 (e.g., 6 °). The second alternative antenna parameters for cell 2 also include cell 2 horizontal 3dB lobe width 2 (e.g., 65 °).
It should be appreciated that the above examples are merely examples of digital weight information in alternative antenna parameters for a cell, and that in particular applications, alternative antenna parameters for a cell may also include more parameters than those shown in the above examples.
For case 1, the first device determines an alternative set of antenna parameters corresponding to the cell of the first device within the range of the cell allowed configuration of the cell. Optionally, the first apparatus further receives an alternative set of antenna parameters corresponding to cells of other network devices from other network devices.
Illustratively, taking an example that the first apparatus is the network device 101 in fig. 1, the set of cells to be optimized includes the cell 1 and the cell 2 of the network device 101, the network device 101 determines the antenna parameter alternative set corresponding to the cell 1 within a range allowed to be configured by the cell 1, and determines the antenna parameter alternative set corresponding to the cell 2 within a range allowed to be configured by the cell 2. If the set of cells to be optimized further includes cell 3 of the network device 105, the network device 105 determines an alternative set of antenna parameters corresponding to cell 3 within a range allowed to be configured by cell 3, and sends the alternative set of antenna parameters corresponding to cell 3 to the network device 101. Accordingly, network device 101 receives the alternative set of antenna parameters corresponding to cell 3.
For case 2, the first device receives an alternative set of antenna parameters corresponding to cells of other devices from other devices.
Illustratively, taking the example that the first apparatus is the computing apparatus 104 in fig. 1, where the set of cells to be optimized includes the cell 1 and the cell 2 of the network device 101, the network device 101 determines the candidate set of antenna parameters corresponding to the cell 1 within the range allowed to be configured by the cell 1, determines the candidate set of antenna parameters corresponding to the cell 2 within the range allowed to be configured by the cell 2, and sends the candidate set of antenna parameters corresponding to the cell 1 and the candidate set of antenna parameters corresponding to the cell 2 to the computing apparatus 104. Accordingly, the computing device 104 receives the alternative set of antenna parameters corresponding to the cell 1 and the alternative set of antenna parameters corresponding to the cell 2. If the set of cells to be optimized further includes cell 3 of the network device 105, the network device 105 determines an alternative set of antenna parameters corresponding to cell 3 within a range allowed to be configured by cell 3, and sends the alternative set of antenna parameters corresponding to cell 3 to the computing device 104. Accordingly, the computing device 104 receives the alternative set of antenna parameters corresponding to cell 3.
S203: the first device acquires measurement information of each of a plurality of terminals.
Wherein a plurality of terminals reside in cells in a set. The plurality of terminals may be all or part of the terminals residing in each cell in the set.
Illustratively, taking the example that the set of cells to be optimized includes cell 1 of network device 101 and cell 3 of network device 105 in fig. 1, where terminal 102 and terminal 103 reside in cell 1, where terminal 106 and terminal 107 reside in cell 3, the plurality of terminals includes terminal 102, terminal 103, terminal 106 and terminal 107; or the plurality of terminals may include terminal 102, terminal 106, and terminal 107; alternatively, the plurality of terminals may include terminal 102 and terminal 107.
One possible design, the measurement information of any one terminal includes the signal quality of each cell measured by the terminal and the arrival direction angle of the terminal with respect to each cell.
Wherein the signal quality of a cell measured by any one terminal may be the reference signal received power (reference signal received power, RSRP) of the cell measured by the terminal. The direction of arrival angle of any one terminal with respect to one cell may include a horizontal direction of arrival angle and a vertical direction of arrival angle, denoted as HDOA and VDOA, respectively. Where HDOA is the angle relative to the cell horizontal normal direction and VDOA is the angle relative to the cell vertical normal direction. The RSRP of a cell measured by a terminal may be denoted as RSRP m,n The horizontal direction of arrival angle and the vertical direction of arrival angle of a terminal with respect to a cell can be respectively referred to as HDOA m.n ，VDOA m.n . Wherein m is the identification of the terminal, and n is the cell identification.
Illustratively, the plurality of terminals include a terminal 102 and a terminal 103, the set of cells to be optimized includes a cell 1 and a cell 2, the terminal 102 resides in the cell 1, the terminal 103 resides in the cell 2 as an example, the measurement information of the terminal 102 includes an RSRP of the cell 1 measured by the terminal 102, an arrival direction angle of the terminal 102 with respect to the cell 1, an RSRP of the cell 2 measured by the terminal 102, and an arrival direction angle of the terminal 102 with respect to the cell 2, and the measurement information of the terminal 103 includes an RSRP of the cell 1 measured by the terminal 103, an arrival direction angle of the terminal 103 with respect to the cell 1, an RSRP of the cell 2 measured by the terminal 103, and an arrival direction angle of the terminal 103 with respect to the cell 2.
The procedure of the first device acquiring measurement information of each of the plurality of terminals in case 1 and case 2, respectively, will be explained below.
For example, for case 1, taking the first apparatus as network device 101 in fig. 1, the set of cells to be optimized includes cell 1 and cell 2 of network device 101, terminal 102 resides in cell 1, terminal 103 resides in cell 2 as an example, and terminal 102 measures RSRP of cell 1 102,1 And RSRP of cell 2 102,2 And sends RSRP to the network device 101 102,1 And RSRP 102,2 The terminal 102 also transmits a sounding reference signal (sounding reference signal, SRS) 1 to the network device 101 through cell 1. Network device 101 measures SRS 1 to obtain the direction of arrival angle of terminal 102 with respect to cell 1, and terminal 102 also transmits SRS 2 to network device 101 through cell 2. The network device 101 measures SRS 2 to obtain the direction of arrival angle of the terminal 102 with respect to cell 2. Similarly, terminal 103 measures the RSRP of cell 1 103,1 RSRP of cell 2 103,2 And sends RSRP to the network device 101 103,1 And RSRP 103,2 Terminal 103 also transmits SRS3 to network device 101 through cell 1. The network device 101 measures SRS3 to obtain the direction of arrival angle of the terminal 103 with respect to cell 1, and the terminal 103 also transmits SRS 4 to the network device 101 through cell 2. The network device 101 measures SRS 4 to obtain the direction of arrival angle of the terminal 103 with respect to cell 2.
For example, in case 2, taking the first device as the computing device 104 in fig. 1, the set of cells to be optimized includes the cell 1 and the cell 2 of the network device 101, where the terminal 102 resides in the cell 1, and the terminal 103 resides in the cell 2, the network device 101 obtains the measurement information of the terminal 102 and the measurement information of the terminal 103 by using the above method, and then sends the measurement information of the terminal 102 and the measurement information of the terminal 103 to the computing device 104. Accordingly, the computing device 104 receives the measurement information of the terminal 102 and the measurement information of the terminal 103.
S204: the first device determines a target antenna parameter of each cell according to the antenna parameter alternative set and the measurement information of each terminal.
One possible implementation manner is that the first device adopts an ant colony algorithm to determine a plurality of iteration parameters in an antenna parameter alternative set, determines a pheromone corresponding to each iteration parameter according to measurement information of each terminal, and determines a target antenna parameter of each cell according to the pheromone corresponding to each iteration parameter.
For example, the first device determines an ant colony algorithm parameter, and determines a plurality of iteration parameters in the antenna parameter alternative set according to the parameter of the ant colony algorithm. Wherein the parameters of the ant colony algorithm comprise at least one of the following: ant number, iteration number, pheromone volatilization factor, pheromone concentration initial value, heuristic function initial value and the like. Wherein the ant number is the number of the plurality of iteration parameters. The iteration times are the execution times of the ant colony algorithm. The pheromone volatilization factor is related to the convergence rate of the ant colony algorithm. The probability that the alternative antenna parameter corresponding to each cell is selected as an iteration parameter is related to the pheromone concentration corresponding to the antenna parameter, and the larger the pheromone concentration is, the higher the probability that the pheromone concentration is selected. The initial value of the pheromone concentration is related to the convergence speed of the ant colony algorithm. The initial values of the pheromone concentration and the initial values of the heuristic function may be empirically set.
For example, for example 1, the first device first determines the iteration parameter 1 in the antenna parameter alternative set corresponding to the cell 1 and the antenna parameter alternative set corresponding to the cell 2 using the ant colony algorithm. The iteration parameter 1 includes a first alternative antenna parameter corresponding to the cell 1 and a first alternative antenna parameter corresponding to the cell 2. Subsequently, the first device determines the pheromone corresponding to the iteration parameter 1 according to the measurement information of each terminal. The first device determines an iteration parameter 2 in the antenna parameter alternative set corresponding to the cell 1 and the antenna parameter alternative set corresponding to the cell 2 by adopting an ant colony algorithm. The iteration parameter 2 includes a first alternative antenna parameter corresponding to the cell 1 and a second alternative antenna parameter corresponding to the cell 2. Subsequently, the first device determines the pheromone corresponding to the iteration parameter 2 according to the measurement information of each terminal, and the like. The first device adopts an ant colony algorithm to determine a plurality of iteration parameters in an antenna parameter alternative set corresponding to a plurality of cells, and after determining the pheromone corresponding to each iteration parameter according to the measurement information of each terminal, the target antenna parameter of each cell can be determined according to the pheromone corresponding to each iteration parameter. It can be appreciated that in the embodiment of the present application, the ant colony algorithm is adopted to determine a plurality of iteration parameters in the antenna parameter alternative set. In practical application, other algorithms can be used to determine the iteration parameters without limitation.
The following describes a specific process of determining the pheromone corresponding to each iteration parameter by the first device according to the measurement information of each terminal. Specifically, the method comprises the following steps:
s2041: the first device determines a signal quality estimated value and a signal-to-interference-and-noise ratio of each terminal under the condition that cells in the set are configured as corresponding iteration parameters according to the measurement information of each terminal.
In one possible implementation manner, the first device determines, according to measurement information of each terminal, a signal quality estimated value of each terminal in a case where a plurality of cells are configured as corresponding iteration parameters, and determines, according to a signal quality estimated value of each terminal in the plurality of terminals, a signal-to-interference-and-noise ratio of each terminal in a case where a cell in the set is configured as a corresponding iteration parameter.
In one possible implementation manner, the first apparatus determines, according to measurement information of each terminal, a signal quality estimated value of each terminal in a case where cells in the set are configured as corresponding iteration parameters, where the signal quality estimated value includes: the first device determines an estimated value of the arrival direction angle of each terminal according to the corresponding arrival direction angle of each terminal relative to each cell, and determines an estimated value of the signal quality of each terminal according to the estimated value of the arrival direction angle of each terminal and the signal quality of each cell measured by each terminal under the condition that the cells in the set are configured as corresponding iteration parameters. In this way, the first apparatus may estimate, by means of coordinate rotation, the estimated value of the direction of arrival angle of each terminal in the case where the cells in the set are configured as the corresponding iteration parameters, and further estimate the estimated value of the signal quality of each terminal in the case where the cells in the set are configured as the corresponding iteration parameters.
First, taking a terminal as an example, a signal quality estimation value of the terminal is introduced in a case that the first device determines that cells in the set are configured as corresponding iteration parameters. In example 2 described below, assuming that the set of cells to be optimized includes cell 1 and cell 2, the first device determines iteration parameter 1 in the antenna parameter alternative set corresponding to cell 1 and the antenna parameter alternative set corresponding to cell 2 using the ant colony algorithm, and determines iteration parameter 2 in the antenna parameter alternative set corresponding to cell 1 and the antenna parameter alternative set corresponding to cell 2 using the ant colony algorithm.
In example 2, the first device determines, according to the corresponding direction of arrival angle of the terminal with respect to the cell 1, an estimated value of the direction of arrival angle of the terminal in a case where the cell 1 is configured as the iteration parameter 1 (e.g., the mechanical azimuth angle of the cell 1 is configured as-40 ° and the mechanical downtilt angle of the cell 1 is configured as 3 °), and determines an estimated value of the signal quality of the terminal according to the estimated value of the direction of arrival angle of the terminal and the signal quality of the cell 1 measured by the terminal.
Specifically, in the case where cell 1 is configured as iteration parameter 1, the arrival direction angle estimation value of the terminal satisfies the following formula:
VDOA m,n,new ＝acos(cosβcosVDOA m,n +sinβcos(HDOA m,n -α)sinVDOA m,n )，
HDOA m,n,new ＝arctan((sin(HDOA m,n -α)sinVDOA m,n )/(cosβsinVDOA m,n cos(HDOA m,n -α)-sinβcosVDOA m,n ))。
wherein VDOA m,n,new In case cell 1 is configured as iteration parameter 1, the vertical direction arrival direction angle estimate of the terminal, HDOA m,n,new In case cell 1 is configured as iteration parameter 1, the horizontal direction arrival direction angle estimate, VDOA, of the terminal m,n For the vertical direction arrival direction angle corresponding to the terminal with respect to cell 1, HDOA m,n Which is the corresponding horizontal direction arrival direction angle of the terminal with respect to cell 1. Alpha = Azim n,new -Azim n ，β＝Tilt n,new -Tilt n 。Azim n,new For iterating the mechanical azimuth of cell 1 included in parameter 1, azim n Tilt, the current mechanical azimuth for cell 1 n,new For iterating the mechanical downtilt of cell 1 included in parameter 1, tilt n Is the current mechanical downtilt of cell 1. Thus, the first device integrates mechanical azimuthal adjustment and mechanical downtilt adjustment for HDOA m,n,new And VDOA m,n,new The influence of (3) is such that the calculated HDOA m,n,new And VDOA m,n,new More accurate. In this example, n is equal to 1, and m is the identity of the terminal.
In case cell 1 is configured as iteration parameter 1, the signal quality estimate of the terminal satisfies the following formula:
wherein RSRP m,n,new In case cell 1 is configured as iteration parameter 1, signal quality estimate, RSRP, of the terminal m,n Cell 1 signal quality measured for terminal, a>To be when the horizontal angle of the terminal reaches the direction angle of HDOA m,n,new The vertical angle of the terminal arrives at the direction angle as VDOA m,n,new And the digital weight information corresponding to the cell 1 is W in Antenna gain at time, < >>To be when the horizontal angle of the terminal reaches the direction angle of HDOA m,n The vertical angle of the terminal arrives at the direction angle as VDOA m,n And the digital weight information corresponding to the cell 1 is W in Antenna gain at that time.
Similarly, the first device may determine the signal quality estimate of the terminal in the case where the cell 2 is configured as the iteration parameter 1 (e.g. the mechanical azimuth angle of the cell 2 is configured as 90 °, the mechanical downtilt angle of the cell 2 is configured as 3 °), determine the signal quality estimate of the terminal in the case where the cell 1 is configured as the iteration parameter 2, and determine the signal quality estimate of the terminal in the case where the cell 2 is configured as the iteration parameter 2.
It will be appreciated that, for each of the plurality of terminals, the first apparatus determines, using the method described above, a signal quality estimate for each terminal in the case where cell 1 is configured as iteration parameter 1, a signal quality estimate for each terminal in the case where cell 2 is configured as iteration parameter 1, a signal quality estimate for each terminal in the case where cell 1 is configured as iteration parameter 2, and a signal quality estimate for each terminal in the case where cell 2 is configured as iteration parameter 2.
One possible implementation, the first device reselects a camping cell for each terminal. For example, for any one terminal, the first device determines a cell corresponding to the maximum value of the signal quality estimation values of the terminal as a camping cell of the terminal.
For example 2 above, if the cell 1 is configured as the iteration parameter 1, the signal quality estimation value of the terminal is RSRP 1, and if the cell 2 is configured as the iteration parameter 1, the signal quality estimation value of the terminal is RSRP 2, and if the RSRP 1 is larger than RSRP 2, the first device determines the cell 1 as the camping cell of the terminal, and if the RSRP 1 is smaller than RSRP 2, the first device determines the cell 2 as the camping cell of the terminal.
It may be appreciated that after the first apparatus determines the signal quality estimate of each of the plurality of terminals, the signal-to-interference-and-noise ratio of each terminal may be determined according to the signal quality estimate of each of the plurality of terminals, where the cells in the set are configured as corresponding iteration parameters.
In a possible implementation manner, in a case that cells in the set are configured as corresponding iteration parameters, the signal-to-interference-and-noise ratio of any one terminal satisfies the following formula:
Wherein SINR m,new Is a collectionIn the case that a certain cell of the plurality of cells is configured as a corresponding iteration parameter, the signal-to-interference-and-noise ratio (RSRP) of any one terminal m,x,new The signal quality estimation value corresponding to the resident cell selected again for the terminal for the first device, x is the identity of the resident cell, RSRP m,y,new Set for signal quality estimate corresponding to cell identified as y cluster Including the identity of the cells in the set of cells to be optimized. N is the noise power.
For example, for example 2 above, if the first device determines cell 1 as the camping cell of the terminal, then in the case where cell 1 and cell 2 are configured as iteration parameters 1, the signal-to-interference-plus-noise ratio of the terminal is SINR m,new ＝RSRP m,1,new -RSRP m,2,new -N。
S2042: the first device determines the pheromone corresponding to each iteration parameter according to the signal quality estimated value and the signal-to-interference-and-noise ratio of each terminal.
In one possible implementation manner, the first device determines a signal quality distribution function corresponding to each iteration parameter according to the signal quality estimated value of each terminal, determines a signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter according to the signal-to-interference-and-noise ratio of each terminal, and determines an pheromone corresponding to each iteration parameter according to the signal quality distribution function corresponding to each iteration parameter and the signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter.
Wherein, any one iteration parameter corresponds to a signal quality distribution function and is used for indicating the signal quality condition of a plurality of terminals under the condition that cells in the set are configured as the iteration parameters. Any one iteration parameter corresponds to a signal-to-interference-and-noise ratio distribution function and is used for indicating the signal-to-interference-and-noise ratio conditions of a plurality of terminals under the condition that cells in a set are configured as iteration parameters.
It will be appreciated that, for any one of the plurality of iteration parameters, the first means may determine, according to the signal quality estimate value of each terminal, a signal quality distribution function corresponding to the first iteration parameter, i.e. the first distribution function f 1 (RSRP) determining a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter, namely the first iteration parameter, according to the signal-to-interference-and-noise ratio of each terminalTwo distribution functions f 2 And determining the pheromone corresponding to the first iteration parameter according to the first distribution function and the second distribution function.
In one possible implementation manner, the first device determines, according to the first distribution function and the second distribution function, a pheromone corresponding to the first iteration parameter, including: the first device acquires first signal quality and first signal-to-interference-and-noise ratio, and determines the pheromone corresponding to the first iteration parameter according to the first signal quality and the first signal-to-interference-and-noise ratio.
The first signal quality is the signal quality corresponding to the first distribution function when the first distribution function is equal to the first value, that is, the input value of the first distribution function when the first signal quality is the output value of the first distribution function. And under the condition that the first signal-to-interference-and-noise ratio is equal to the second numerical value, the signal-to-interference-and-noise ratio corresponding to the second distribution function, namely under the condition that the output value of the first signal-to-interference-and-noise ratio is the second numerical value, the input value of the second distribution function.
For example, if the first and second values are both 0.5, the first device selects f 1 (RSRP) is equal to the corresponding RSRP of 0.5, resulting in a first signal quality RSRP cdf . First device selection f 2 The corresponding SINR (SINR) equal to 0.5 results in a first SINR (signal to interference plus noise ratio) cdf . The pheromone corresponding to the first iteration parameter satisfies the following formula: eta=af (RSRP) cdf )+bf(SINR cdf ). Wherein a and b are each f (RSRP) cdf ) Sum f (SINR) cdf ) For example, a and b are both 0.5. Where f (·) can be a normalization function.
It can be appreciated that in the above process, the first distribution function and the second distribution function are respectively equal to a value, so as to obtain the corresponding first signal quality and the first signal-to-interference-and-noise ratio. In practical application, in order to comprehensively consider the performances of the terminals at each point of the near, middle and far points, more terminals can improve the performances, and the first distribution function and the second distribution function can be respectively equal to a plurality of numerical values. The following description will take an example in which the first distribution function and the second distribution function are equal to two values, respectively.
In one possible implementation manner, the first device determines, according to the first signal quality and the first signal-to-interference-and-noise ratio, a pheromone corresponding to the first iteration parameter, including: the first device acquires the second signal quality and the second signal-to-interference-and-noise ratio, and determines the pheromone corresponding to the first iteration parameter according to the first signal quality, the first signal-to-interference-and-noise ratio, the second signal quality and the second signal-to-interference-and-noise ratio.
And when the second signal quality is equal to the third value, the signal quality corresponding to the first distribution function, that is, when the second signal quality is equal to the third value, the output value of the first distribution function is equal to the input value of the first distribution function. And when the second signal-to-interference-and-noise ratio is equal to the fourth value, the signal-to-interference-and-noise ratio corresponding to the second distribution function, namely, when the second signal-to-interference-and-noise ratio is the fourth value, the output value of the second distribution function is the input value of the second distribution function.
For example, if the first and second values are both 0.5 and the third and fourth values are both 0.1, the first device selects f 1 (RSRP) is equal to the corresponding RSRP of 0.5, resulting in a first signal quality RSRP cdf05 Select f 1 (RSRP) is equal to the corresponding RSRP of 0.1, resulting in a second signal quality RSRP cdf01 . First device selection f 2 The (SINR) is equal to the corresponding SINR of 0.5, and the first SINR is obtained cdf05 Select f 2 The (SINR) is equal to the SINR corresponding to 0.1, and the second SINR is obtained cdf01 . The pheromone corresponding to the first iteration parameter satisfies the following formula: eta=a 05 f(RSRP cdf05 )+a 01 f(RSRP cdf01 )+b 05 f(SINR cdf05 )+b 01 f(SINR cdf01 ). Wherein a is 05 、a 01 、b 05 And b 01 Is a weight factor, for example, all 0.25.
It can be understood that, after multiple iterations, the first device may obtain the pheromone corresponding to each iteration parameter in the multiple iteration parameters, and determine the target antenna parameter of each cell according to the pheromone corresponding to each iteration parameter. For example, the first device determines, as the target antenna parameter of each cell, the candidate antenna parameter of each cell included in the iteration parameter corresponding to the largest pheromone among the pheromones corresponding to the plurality of iteration parameters.
For example, if the iteration parameter 1 includes a first alternative antenna parameter corresponding to the cell 1 and a first alternative antenna parameter corresponding to the cell 2, and the iteration parameter 2 includes a first alternative antenna parameter corresponding to the cell 1 and a second alternative antenna parameter corresponding to the cell 2, where an pheromone corresponding to the iteration parameter 1 is eta1, an pheromone corresponding to the iteration parameter 2 is eta2, and eta2> eta1, the first device determines the first alternative antenna parameter corresponding to the cell 1 as a target antenna parameter of the cell 1, and determines the second alternative antenna parameter corresponding to the cell 2 as a target antenna parameter of the cell 2.
It will be appreciated that after the first device determines the target antenna parameters for each cell, the first device may configure the cell according to the target antenna parameters. Optionally, the first apparatus sends target antenna parameters corresponding to other network devices.
For example, for case 1, if the set of cells to be optimized includes cell 1 of network device 101, and the target antenna parameters of cell 1 include the antenna mechanical azimuth angle (70 °) of cell 1 and the antenna mechanical downtilt angle (6 °) of cell 1, network device 101 sets the antenna mechanical azimuth angle of cell 1 to 70 °, and sets the antenna mechanical downtilt angle of cell 1 to 6 °. If the target antenna parameters of cell 1 further include the azimuth angle (10 °) of cell 1 and the downtilt angle (5 °) of cell 1, the network device 101 further sets the azimuth angle of cell 1 to 10 ° and the downtilt angle of cell 1 to 5 °. If the set of cells to be optimized further includes cell 3 of the network device 105, the network device 101 sends the target antenna parameter of cell 3 to the network device 105, so that the network device 105 configures cell 3 according to the target antenna parameter of cell 3.
For example, for case 2, if the set of cells to be optimized includes cell 1 of network device 101, computing apparatus 104 sends the target antenna parameters of cell 1 to network device 101, such that network device 101 configures cell 1 according to the target antenna parameters of cell 1. If the set of cells to be optimized further comprises cell 3 of the network device 105, the computing means 104 sends the target antenna parameters of cell 3 to the network device 105, such that the network device 105 configures cell 3 according to the target antenna parameters of cell 3.
Based on the method shown in fig. 2, the first device may determine the target antenna parameter for each cell in the set, which does not consume large manpower and material resources, and because the signal quality of each cell and the arrival direction angle of the terminal relative to each cell measured by the terminal in each cell in the set are considered when determining the target antenna parameter, the determined target antenna parameter is reasonable. In this way, after optimizing the corresponding cell according to the target antenna parameter, the signal quality of the terminal in the cell can be improved. It can be understood that if any one of the alternative antenna parameters further includes digital weight information corresponding to the cell, the first device may adjust the antenna mechanical angle and the digital weight information at the same time, so as to obtain better cell coverage.
Optionally, if any one of the alternative antenna parameters does not include the digital weight information corresponding to the cell, after S204, the method shown in fig. 2 further includes the following steps, which may specifically be shown in fig. 3.
S205: the first device acquires a plurality of pieces of alternative digital weight information corresponding to each cell in the set.
The candidate digital weight information corresponding to any one of the cells to be optimized may include an azimuth angle of the cell and/or a downtilt angle of the cell. Optionally, the alternative digital weight information corresponding to any one cell may further include a horizontal lobe width of the cell and/or a vertical lobe width of the cell. The description of the azimuth angle of the cell, the downtilt angle of the cell, the horizontal lobe width of the cell, and the vertical lobe width of the cell can be referred to in S202.
For case 1, the first device determines a plurality of alternative digital weight information corresponding to the cell of the first device within a range of cell allowed configuration of the cell. Optionally, the first apparatus further receives a plurality of candidate digital weight information corresponding to cells of other network devices from other network devices.
For case 2, the first device receives a plurality of alternative digital weight information corresponding to cells of other devices from other devices.
S206: the first device adopts an ant colony algorithm to determine a plurality of iteration information in a plurality of alternative digital weight information, and determines the pheromone corresponding to each iteration information according to the measurement information of each terminal.
S206 is similar to the process that the first device in S204 adopts the ant colony algorithm to determine a plurality of iteration parameters in the antenna parameter alternative set, and determines the pheromone corresponding to each iteration parameter according to the measurement information of each terminal, and reference can be made to the corresponding description in S204. Differently, in case it is determined that each cell is configured as the corresponding iteration information, azim in S204 n,new Replacing the mechanical azimuth in the target antenna parameters determined by the first device, tilt in S204 n,new Instead of the mechanical downtilt in the target antenna parameters determined by the first device.
S207: the first device determines the target digital weight information of each cell according to the pheromone corresponding to each iteration information.
It can be understood that, after multiple iterations, the first device may obtain the pheromone corresponding to each iteration information in the multiple iteration information, and determine the target digital weight information of each cell according to the pheromone corresponding to each iteration information. For example, the first device determines, as target digital weight information of each cell, candidate digital weight information of each cell included in iteration information corresponding to a largest one of the plurality of iteration information.
Optionally, as shown in fig. 4, S201 may include the steps of:
s2011: the first device acquires a first cell.
Wherein the duty ratio of the terminal in the weak coverage area of the first cell is greater than or equal to a preset threshold. For example, a ratio of a number of all terminals in the weak coverage of the first cell to a number of all terminals in the first cell is greater than or equal to a preset threshold. Or, in the partial terminals in the first cell, a ratio of the number of terminals in the weak coverage area of the first cell to the number of the partial terminals is greater than or equal to a preset threshold. The preset threshold may be set as desired, for example, the preset threshold is 0.5.
In one possible implementation, S2011 may include the following steps:
S2011A: the first device acquires N pieces of digital weight information corresponding to the third cell.
Wherein N is an integer greater than 1. The digital weight information may refer to the corresponding introduction in S202.
The first device determines N pieces of digital weight information, such as W, within the range of digital weight information allowed to be configured by the third cell 1 、W 2 …W n . Arbitrary digital weight information W i Including the azimuth angle of the third cell and/or the downtilt angle of the third cell. Alternatively, W i The horizontal lobe width of the third cell and/or the vertical lobe width of the third cell may also be included. i is an integer greater than 0 and less than N.
For case 1, the network device 101 determines N pieces of digital weight information corresponding to the third cell within a range of the third cell permission configuration. Wherein the third cell may be a cell of the network device 101. Or, the network device 101 receives N pieces of digital weight information corresponding to the third cell from the other network devices.
For case 2, the first device receives N pieces of digital weight information corresponding to the third cell of the other device from the other device.
S2011B: the first device acquires N antenna gains corresponding to the N digital weight information according to the N digital weight information.
Exemplary, if W i Including the azimuth angle (0 °), the downtilt angle (0 °) of the third cell, the horizontal 3dB lobe width (65 °) of the third cell, and the vertical 3dB lobe width (6 °) of the third cell, the first device is based on the antenna element pattern and W i Can determine W i Each of the lower (horizontal angle a h Vertical angle a v ) Combining corresponding antenna gainsThus obtainingW is W i Corresponding antenna gain. Wherein a is h Is an angle with respect to the horizontal normal direction, as can be seen in fig. 6. a, a v Is an angle with respect to the vertical normal direction. The above operation is performed on each digital weight information in the N digital weight information, so that the antenna gain corresponding to each digital weight information can be obtained, and the N antenna gains are obtained.
S2011C: the first device obtains the weak coverage of the third cell according to the N antenna gains.
In one possible implementation manner, the first device determines, according to the N antenna gains, N horizontal coverage areas and N vertical coverage areas corresponding to the N digital weight information, and determines, according to the N horizontal coverage areas and the N vertical coverage areas, a weak coverage area of the third cell.
One possible design is that any one horizontal coverage area is greater than or equal to a first azimuth angle and less than or equal to a second azimuth angle.
It can be understood that, according to a certain antenna gain, the first device can obtain the horizontal coverage corresponding to the antenna gain. For example, the first device is according to W i Corresponding antenna gain determination W i Antenna gain curve in the vertical normal direction, i.e. fixed a v 0 and traversing all a from small to large h The first antenna gain diagram shown in fig. 7 is obtained, the minimum horizontal angle among the horizontal angles in which the antenna gain in the first antenna gain diagram is greater than or equal to the first threshold (such as the gain threshold in fig. 7) is determined as the first azimuth angle, and the maximum horizontal angle among the horizontal angles in which the antenna gain in the first antenna gain diagram is greater than or equal to the first threshold is determined as the second azimuth angle. The first device performs the above operation on the antenna gain corresponding to each digital weight information, so that N horizontal coverage areas can be obtained, that is, the coverage areas obtain N first azimuth angles and N second azimuth angles.
In one possible implementation, the first device determines a smallest azimuth among the N first azimuths and determines a largest azimuth among the N second azimuths. The weak coverage of the third cell is less than or equal to the minimum azimuth and greater than or equal to the maximum azimuth.
One possible design is that any one vertical coverage area is greater than or equal to the first downtilt angle and less than or equal to the second downtilt angle.
It can be understood that, according to a certain antenna gain, the first device can obtain the vertical coverage corresponding to the antenna gain. For example, the first device is according to W i Corresponding antenna gain determination W i The antenna gain curve in the horizontal normal direction, i.e. fixed a h 0 and traversing all a from small to large v And obtaining a second antenna gain diagram, determining the smallest vertical angle among the vertical angles with the antenna gain larger than or equal to a second threshold in the second antenna gain diagram as a first downward inclination angle, and determining the largest vertical angle among the vertical angles with the antenna gain larger than or equal to the second threshold in the second antenna gain diagram as a second downward inclination angle. The first device executes the operation on the antenna gain corresponding to each digital weight information, so that N vertical coverage ranges can be obtained, and N first dip angles and N second dip angles are obtained.
In one possible implementation, the first device determines a minimum downtilt angle among the N first downtilt angles and determines a maximum downtilt angle among the N second downtilt angles. The weak coverage of the third cell is less than or equal to the minimum downtilt and greater than or equal to the maximum downtilt.
S2011D: if the duty ratio of the terminal in the weak coverage area of the third cell is greater than or equal to a preset threshold value, the first device determines that the third cell is the first cell.
For example, in case 1, if the third cell is a cell of the network device 101, the network device 101 sends SRS to the plurality of terminals in the third cell to perform measurement, so as to obtain the DOA information of each of the plurality of terminals. Wherein the plurality of terminals may comprise all or part of the terminals in the third cell. The DOA information includes a horizontal DOA and a vertical DOA. If the horizontal direction DOA or the vertical direction DOA of a terminal is located in the weak coverage area of the third cell, for example, the horizontal direction DOA of the terminal is smaller than or equal to the minimum azimuth and greater than or equal to the maximum azimuth, and/or the vertical direction DOA of the terminal is smaller than or equal to the minimum downtilt and greater than or equal to the maximum downtilt, the terminal is a terminal in the weak coverage area of the third cell. If the ratio of the number of terminals in the weak coverage area of the third cell to the number of the plurality of terminals is greater than or equal to a preset threshold, the first device determines that the third cell is the first cell.
For example, in case 1, if the third cell is a cell of the network device 105, the network device 101 sends information of the weak coverage of the third cell to the network device 105, and the network device 105 determines information of a terminal in the weak coverage of the third cell and sends the information to the network device 101. Wherein the information of the terminal in the weak coverage of the third cell includes a ratio of the number of terminals in the weak coverage of the third cell to the number of the plurality of terminals, or includes the number of terminals in the weak coverage of the third cell and the number of the plurality of terminals. After receiving the information of the terminal in the weak coverage area of the third cell, the network device 101 may determine whether the third cell is the first cell. Alternatively, the network device 105 may itself determine whether the third cell is the first cell.
For example, in case 2, if the third cell is a cell of the network device 101, the computing apparatus 104 sends information of the weak coverage of the third cell to the network device 101, and the network device 101 determines information of a terminal in the weak coverage of the third cell and sends the information to the computing apparatus 104. Wherein the information of the terminal in the weak coverage of the third cell includes a ratio of the number of terminals in the weak coverage of the third cell to the number of the plurality of terminals, or includes the number of terminals in the weak coverage of the third cell and the number of the plurality of terminals. After receiving the information of the terminal in the weak coverage area of the third cell, the computing device 104 may determine whether the third cell is the first cell. Alternatively, the network device 101 may determine itself whether the third cell is the first cell. The procedure in which the third cell is a cell of the network device 105 is similar to the procedure described above, and will not be described again.
S2012: the first device classifies the first cell and the second cell into a set of cells to be optimized.
Wherein the second cell comprises a cell co-sited with the first cell and/or a cell adjacent to the first cell. The cell co-sited with the first cell comprises the same cell as the network device to which the first cell belongs. The cells adjacent to the first cell include cells geographically adjacent to the first cell. Further, the second cell is co-frequency with the first cell.
It may be appreciated that, through S2011-S2012, the first device may acquire the first cell and assign the first cell and the second cell to the set of cells to be optimized. In this way, the first device can combine the first cell and the second cell to determine the target antenna parameters, so that interference between the first cell and the second cell is strictly controlled while the cell coverage problem is optimized, and the signal quality of the terminal is better improved.
As shown in fig. 5, a method for obtaining a cell to be optimized according to an embodiment of the present application may include the following steps:
s501: the first device acquires N pieces of digital weight information corresponding to the first cell.
S502: the first device acquires N antenna gains corresponding to the N digital weight information according to the N digital weight information.
S503: the first device obtains weak coverage of the first cell according to the N antenna gains.
The specific processes of S501-S503 are similar to those of S2011A-S2011C, and reference may be made to corresponding descriptions in S2011A-S2011C, which are not repeated herein.
S504: the first device determines the first cell as a cell to be optimized according to the information of the terminal in the weak coverage area of the first cell.
The information of the terminal in the weak coverage of the first cell may include a duty ratio of the terminal in the weak coverage of the first cell or the number of terminals in the weak coverage of the first cell.
For example, if the duty ratio of the terminal in the weak coverage area of the first cell is greater than or equal to a preset threshold value, the first cell is determined to be the cell to be optimized. Or, the number of terminals in the weak coverage area of the first cell is greater than or equal to a preset threshold.
Based on the method shown in fig. 5, the first device may obtain N digital weight information corresponding to the first cell, obtain N antenna gains corresponding to the N digital weight information according to the N digital weight information, obtain a weak coverage area of the first cell according to the N antenna gains, and determine that the first cell is a cell to be optimized according to information of a terminal in the first cell within the coverage area. Therefore, the first device can identify the cell to be optimized so as to adjust the parameters of the cell to be optimized, reduce the weak coverage of the cell to be optimized and improve the signal quality of the terminal in the cell.
The embodiment of the present application may divide the functional modules or functional units of the determining device of the antenna parameter according to the above method example, for example, each functional module or functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware, or in software functional modules or functional units. The division of the modules or units in the embodiments of the present application is merely a logic function division, and other division manners may be implemented in practice.
As shown in fig. 8, a schematic structural diagram of an apparatus for determining antenna parameters according to an embodiment of the present application is provided, where the apparatus includes: an acquisition module 801 and a processing module 802.
The acquiring module 801 is configured to acquire a set of cells to be optimized; the obtaining module 801 is further configured to obtain an antenna parameter alternative set corresponding to each cell in the set, where the antenna parameter alternative set corresponding to any one cell includes an antenna mechanical angle of the cell; the acquiring module 801 is further configured to acquire measurement information of each of a plurality of terminals, where the plurality of terminals reside in cells in a set, and the measurement information of any one terminal includes a signal quality of each cell measured by the terminal and an arrival direction angle of the terminal with respect to each cell; a processing module 802, configured to determine a target antenna parameter of each cell according to the antenna parameter alternative set and measurement information of each terminal.
In a possible implementation manner, the processing module 802 is specifically configured to determine a plurality of iteration parameters in the antenna parameter alternative set by using an ant colony algorithm, and determine, according to measurement information of each terminal, an pheromone corresponding to each iteration parameter; the processing module 802 is further specifically configured to determine a target antenna parameter of each cell according to the pheromone corresponding to each iteration parameter.
In a possible implementation manner, the processing module 802 is further specifically configured to determine, according to measurement information of each terminal, a signal quality estimated value and a signal-to-interference-and-noise ratio of each terminal in a case that cells in the set are configured as corresponding iteration parameters; the processing module 802 is further specifically configured to determine, according to the signal quality estimated value and the signal-to-interference-and-noise ratio of each terminal, a pheromone corresponding to each iteration parameter.
In a possible implementation manner, the processing module 802 is further specifically configured to determine, according to measurement information of each terminal, a signal quality estimated value of each terminal in a case where the plurality of cells are configured as corresponding iteration parameters; the processing module 802 is further specifically configured to determine, according to the signal quality estimated value of each of the plurality of terminals, a signal-to-interference-and-noise ratio of each terminal in a case where the cells in the set are configured as corresponding iteration parameters.
In a possible implementation manner, the processing module 802 is further specifically configured to determine, according to a corresponding direction of arrival angle of each terminal with respect to each cell, an estimated value of the direction of arrival angle of each terminal in a case where the cells in the set are configured as corresponding iteration parameters; the processing module 802 is further specifically configured to determine a signal quality estimation value of each terminal according to the estimated direction of arrival angle value of each terminal and the signal quality of each cell measured by each terminal.
In a possible implementation manner, the processing module 802 is further specifically configured to determine, according to the signal quality estimated value of each terminal, a signal quality distribution function corresponding to each iteration parameter, where any one iteration parameter corresponds to the signal quality distribution function and is used to indicate signal quality conditions of a plurality of terminals when a cell in the set is configured as an iteration parameter; the processing module 802 is further specifically configured to determine, according to a signal-to-interference-and-noise ratio of each terminal, a signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter, where any one iteration parameter corresponds to the signal-to-interference-and-noise ratio distribution function, and is used to indicate a signal-to-interference-and-noise ratio condition of a plurality of terminals when a cell in a set is configured as an iteration parameter; the processing module 802 is further specifically configured to determine the pheromone corresponding to each iteration parameter according to the signal quality distribution function corresponding to each iteration parameter and the signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter.
In one possible implementation manner, for any first iteration parameter of the multiple iteration parameters, the processing module 802 is further specifically configured to obtain a first signal quality, where the first signal quality is an input value of a signal quality distribution function corresponding to the first iteration parameter when an output value of the signal quality distribution function corresponding to the first iteration parameter is a first value; the processing module 802 is further specifically configured to obtain a first signal-to-interference-and-noise ratio, where the first signal-to-interference-and-noise ratio is an input value of the signal-to-interference-and-noise ratio corresponding to the first iteration parameter when the output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter is a second value; the processing module 802 is further specifically configured to determine, according to the first signal quality and the first signal-to-interference-and-noise ratio, a pheromone corresponding to the first iteration parameter.
In a possible implementation manner, the processing module 802 is further specifically configured to obtain a second signal quality, where the second signal quality is an input value of the signal quality distribution function corresponding to the first iteration parameter when the output value of the signal quality distribution function corresponding to the first iteration parameter is a third value; the processing module 802 is further specifically configured to obtain a second signal-to-interference-and-noise ratio, where the second signal-to-interference-and-noise ratio is an input value of the signal-to-interference-and-noise ratio corresponding to the first iteration parameter when the output value of the signal-to-interference-and-noise ratio corresponding to the first iteration parameter is a fourth value; the processing module 802 is further specifically configured to determine the pheromone corresponding to the first iteration parameter according to the first signal quality, the first signal-to-interference-and-noise ratio, the second signal quality and the second signal-to-interference-and-noise ratio.
In one possible implementation, the antenna mechanical angle of the cell includes an antenna mechanical azimuth angle of the cell and an antenna mechanical downtilt angle of the cell.
In one possible implementation, any one of the antenna parameters further includes digital weight information corresponding to the cell.
In a possible implementation manner, the obtaining module 801 is further configured to obtain a plurality of candidate digital weight information corresponding to each cell in the set; the processing module 802 is further configured to determine a plurality of iteration information in a plurality of candidate digital weight information by using an ant colony algorithm, and determine an pheromone corresponding to each iteration information according to measurement information of each terminal; the processing module 802 is further configured to determine target digital weight information of each cell according to the pheromone corresponding to each iteration information.
In a possible implementation manner, the obtaining module 801 is specifically configured to obtain a first cell, where a duty ratio of a terminal in a weak coverage area of the first cell is greater than or equal to a preset threshold; the obtaining module 801 is further specifically configured to assign the first cell and a second cell to a set of cells to be optimized, where the second cell includes a cell co-sited with the first cell and/or a cell adjacent to the first cell.
In a possible implementation manner, the obtaining module 801 is further specifically configured to obtain N digital weight information corresponding to the third cell, where N is an integer greater than 1; the acquiring module 801 is further specifically configured to acquire N antenna gains corresponding to the N digital weight information according to the N digital weight information; the obtaining module 801 is further specifically configured to obtain a weak coverage area of the third cell according to the N antenna gains; the obtaining module 801 is further specifically configured to determine that the third cell is the first cell if the duty ratio of the terminal in the weak coverage area of the third cell is greater than or equal to a preset threshold.
In one possible implementation, the processing module 802 is specifically configured to determine, according to N antenna gains, N horizontal coverage ranges and N vertical coverage ranges corresponding to N digital weight information; the processing module 802 is further specifically configured to determine the weak coverage of the third cell according to the N horizontal coverage ranges and the N vertical coverage ranges.
In one possible implementation, any one of the horizontal coverage areas is greater than or equal to a first azimuth angle and less than or equal to a second azimuth angle; the processing module 802 is further specifically configured to determine a smallest azimuth angle among the N first azimuth angles, determine a largest azimuth angle among the N second azimuth angles, and the weak coverage area of the third cell is smaller than or equal to the smallest azimuth angle and is larger than or equal to the largest azimuth angle.
In one possible implementation, any one of the vertical coverage ranges is greater than or equal to the first downtilt angle and less than or equal to the second downtilt angle; the processing module 802 is further specifically configured to determine a minimum downtilt angle from the N first downtilt angles, determine a maximum downtilt angle from the N second downtilt angles, and the weak coverage area of the third cell is less than or equal to the minimum downtilt angle and is greater than or equal to the maximum downtilt angle.
When implemented in hardware, the acquisition module 801 in the embodiments of the present application may be integrated on a communication interface, and the processing module 802 may be integrated on a processor. Alternatively, both the acquisition module 801 and the processing module 802 are integrated on a processor. A specific implementation is shown in fig. 9.
Fig. 9 shows a further possible structural schematic diagram of the antenna parameter determination device involved in the above-described embodiment. The device for determining the antenna parameters comprises: a processor 902. Optionally, the apparatus further comprises a communication interface 903. The processor 902 is configured to control and manage the actions of the means for determining antenna parameters, e.g., performing the steps performed by the processing module 802 described above, and/or for performing other processes of the techniques described herein. The communication interface 903 is used to support communication between the determining device of the antenna parameter and other network entities, for example, to perform the steps performed by the communication unit 202. Optionally, the determining means of the antenna parameter may further comprise a memory 901 and a bus 904, the memory 901 being used for storing program codes and data of the determining means of the antenna parameter.
Wherein the memory 901 may be a memory or the like in the determination means of the antenna parameters, which may include a volatile memory, such as a random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk or solid state disk; the memory may also comprise a combination of the above types of memories.
The processor 902 may be implemented or realized with the various illustrative logical blocks, modules, and circuits described in connection with the present disclosure. The processor may be a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. The processor may also be a combination that performs the function of a computation, e.g., a combination comprising one or more microprocessors, a combination of a DSP and a microprocessor, etc.
Bus 904 may be an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus or the like. The bus 904 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 9, but not only one bus or one type of bus.
Fig. 10 is a schematic structural diagram of a chip 100 according to an embodiment of the present application. The chip 100 includes one or more (including two) processors 1010. Optionally, the chip 100 further comprises a communication interface 1030.
Optionally, the chip 100 further includes a memory 1040, which may include read-only memory and random access memory, and provides operating instructions and data to the processor 1010. A portion of memory 1040 may also include non-volatile random access memory (NVRAM).
In some implementations, the memory 1040 stores elements, execution modules or data structures, or a subset thereof, or an extended set thereof.
In the embodiment of the present application, the corresponding operation is performed by calling the operation instruction stored in the memory 1040 (the operation instruction may be stored in the operating system).
Wherein the processor 1010 may implement or execute the various exemplary logic blocks, units and circuits described in connection with the present disclosure. The processor may be a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, units and circuits described in connection with this disclosure. A processor may also be a combination that performs computing functions, e.g., including one or more microprocessors, a combination of a DSP and a microprocessor, and the like.
Memory 1040 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk or solid state disk; the memory may also comprise a combination of the above types of memories.
Bus 1020 may be an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus or the like. The bus 1020 may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one line is shown in fig. 10, but not only one bus or one type of bus.
From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above. The specific working processes of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which are not described herein.
The present application provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of determining antenna parameters in the method embodiments described above.
The embodiment of the application also provides a computer readable storage medium, in which instructions are stored, which when executed on a computer, cause the computer to execute the method for determining the antenna parameters in the method flow shown in the method embodiment.
The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access Memory (Random Access Memory, RAM), a Read-Only Memory (ROM), an erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a register, a hard disk, 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, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuit, ASIC). In the context of the present application, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
Since the determining apparatus, the computer-readable storage medium and the computer program product of the antenna parameter in the embodiments of the present application may be applied to the above-mentioned method, the technical effects that can be obtained by the determining apparatus, the computer-readable storage medium and the computer program product may also refer to the above-mentioned method embodiments, and the embodiments of the present application are not repeated herein.
The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (18)

1. A method for determining antenna parameters, the method comprising:
acquiring a set of cells to be optimized;
acquiring an antenna parameter alternative set corresponding to each cell in the set, wherein the antenna parameter alternative set corresponding to any cell comprises an antenna mechanical angle of the cell;
acquiring measurement information of each terminal in a plurality of terminals, wherein the plurality of terminals reside in cells in the set, and the measurement information of any one terminal comprises the signal quality of each cell measured by the terminal and the arrival direction angle of the terminal relative to each cell;
And determining the target antenna parameters of each cell according to the antenna parameter alternative set and the measurement information of each terminal.
2. The method of claim 1, wherein said determining the target antenna parameters for each cell based on the alternative set of antenna parameters and the measurement information for each terminal comprises:
determining a plurality of iteration parameters in the antenna parameter alternative set by adopting an ant colony algorithm, and determining pheromones corresponding to each iteration parameter according to the measurement information of each terminal;
and determining the target antenna parameters of each cell according to the pheromone corresponding to each iteration parameter.
3. The method according to claim 2, wherein the determining the pheromone corresponding to each iteration parameter according to the measurement information of each terminal includes:
according to the measurement information of each terminal, determining a signal quality estimated value and a signal-to-interference-and-noise ratio of each terminal under the condition that cells in the set are configured as corresponding iteration parameters;
and determining the pheromone corresponding to each iteration parameter according to the signal quality estimated value of each terminal and the signal-to-interference-and-noise ratio.
4. A method according to claim 3, wherein said determining, based on said measurement information of each terminal, a signal quality estimate and a signal-to-interference-and-noise ratio for each terminal if cells in said set are configured as corresponding iteration parameters comprises:
determining a signal quality estimated value of each terminal under the condition that the cells are configured as corresponding iteration parameters according to the measurement information of each terminal;
and determining the signal-to-interference-and-noise ratio of each terminal under the condition that the cells in the set are configured as corresponding iteration parameters according to the signal quality estimated value of each terminal in the plurality of terminals.
5. The method according to claim 4, wherein the determining the signal quality estimate for each terminal if the cells in the set are configured as corresponding iteration parameters based on the measurement information for each terminal comprises:
determining an estimated value of the arrival direction angle of each terminal under the condition that the cells in the set are configured as corresponding iteration parameters according to the corresponding arrival direction angle of each terminal relative to each cell;
And determining the signal quality estimated value of each terminal according to the estimated value of the arrival direction angle of each terminal and the signal quality of each cell measured by each terminal.
6. The method according to claim 3, 4 or 5, wherein said determining the pheromone corresponding to each iteration parameter according to the signal quality estimation value of each terminal and the signal-to-interference-and-noise ratio comprises:
determining a signal quality distribution function corresponding to each iteration parameter according to the signal quality estimation value of each terminal, wherein the signal quality distribution function corresponding to any one iteration parameter is used for indicating the signal quality condition of the plurality of terminals under the condition that cells in the set are configured as the iteration parameters;
determining a signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter according to the signal-to-interference-and-noise ratio of each terminal, wherein the signal-to-interference-and-noise ratio distribution function corresponding to any one iteration parameter is used for indicating the signal-to-interference-and-noise ratio condition of the plurality of terminals under the condition that cells in the set are configured as the iteration parameters;
and determining the pheromone corresponding to each iteration parameter according to the signal quality distribution function corresponding to each iteration parameter and the signal-to-interference-and-noise ratio distribution function corresponding to each iteration parameter.
7. The method of claim 6, wherein for any first iteration parameter of the plurality of iteration parameters, determining the pheromone corresponding to the first iteration parameter according to the signal quality distribution function corresponding to the first iteration parameter and the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter comprises:
acquiring first signal quality, wherein the first signal quality is an input value of a signal quality distribution function corresponding to the first iteration parameter under the condition that an output value of the signal quality distribution function corresponding to the first iteration parameter is a first numerical value;
acquiring a first signal-to-interference-and-noise ratio, wherein the first signal-to-interference-and-noise ratio is an input value of a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter under the condition that an output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter is a second value;
and determining the pheromone corresponding to the first iteration parameter according to the first signal quality and the first signal-to-interference-and-noise ratio.
8. The method of claim 7, wherein determining the pheromone corresponding to the first iteration parameter according to the first signal quality and the first signal-to-interference-and-noise ratio comprises:
Acquiring second signal quality, wherein the second signal quality is an input value of a signal quality distribution function corresponding to the first iteration parameter under the condition that the output value of the signal quality distribution function corresponding to the first iteration parameter is a third numerical value;
acquiring a second signal-to-interference-and-noise ratio, wherein the second signal-to-interference-and-noise ratio is an input value of a signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter under the condition that an output value of the signal-to-interference-and-noise ratio distribution function corresponding to the first iteration parameter is a fourth value;
and determining the pheromone corresponding to the first iteration parameter according to the first signal quality, the first signal-to-interference-and-noise ratio, the second signal quality and the second signal-to-interference-and-noise ratio.
9. The method of any of claims 1-5, 7 or 8, wherein the antenna mechanical angle of the cell comprises an antenna mechanical azimuth angle of the cell and an antenna mechanical downtilt angle of the cell.
10. The method according to any one of claims 1-5, 7 or 8, wherein any one of the alternative antenna parameters further comprises digital weight information corresponding to the cell.
11. The method of any one of claims 1-5, 7 or 8, further comprising:
Acquiring a plurality of pieces of alternative digital weight information corresponding to each cell in the set;
determining a plurality of iteration information in the plurality of candidate digital weight information by adopting an ant colony algorithm, and determining an pheromone corresponding to each iteration information according to the measurement information of each terminal;
and determining the target digital weight information of each cell according to the pheromone corresponding to each piece of iteration information.
12. The method according to any of claims 1-5, 7 or 8, wherein the obtaining a set of cells to be optimized comprises:
acquiring a first cell, wherein the duty ratio of a terminal in the weak coverage area of the first cell is larger than or equal to a preset threshold value;
and classifying the first cell and a second cell into the set of cells to be optimized, wherein the second cell comprises a cell co-sited with the first cell and/or a cell adjacent to the first cell.
13. The method of claim 12, wherein the acquiring the first cell comprises:
acquiring N pieces of digital weight information corresponding to a third cell, wherein N is an integer greater than 1;
acquiring N antenna gains corresponding to the N digital weight information according to the N digital weight information;
Acquiring the weak coverage area of the third cell according to the N antenna gains;
and if the duty ratio of the terminal in the weak coverage area of the third cell is greater than or equal to the preset threshold value, determining that the third cell is the first cell.
14. The method of claim 13, wherein the obtaining the weak coverage of the third cell according to the N antenna gains comprises:
according to the N antenna gains, N horizontal coverage areas and N vertical coverage areas corresponding to the N digital weight information are determined;
and determining the weak coverage of the third cell according to the N horizontal coverage areas and the N vertical coverage areas.
15. The method of claim 14, wherein any one horizontal coverage area is greater than or equal to a first azimuth angle and less than or equal to a second azimuth angle;
the determining the weak coverage of the third cell according to the N horizontal coverage areas and the N vertical coverage areas includes:
the method comprises the steps of determining a smallest azimuth angle in N first azimuth angles, determining a largest azimuth angle in N second azimuth angles, wherein the weak coverage area of the third cell is smaller than or equal to the smallest azimuth angle and larger than or equal to the largest azimuth angle.
16. The method of claim 15, wherein any one of the vertical coverage areas is greater than or equal to a first downtilt angle and less than or equal to a second downtilt angle;
the determining the weak coverage of the third cell according to the N horizontal coverage areas and the N vertical coverage areas further includes:
the minimum downtilt angle is determined among the N first downtilt angles, the maximum downtilt angle is determined among the N second downtilt angles, and the weak coverage of the third cell is less than or equal to the minimum downtilt angle and greater than or equal to the maximum downtilt angle.
17. An apparatus for determining antenna parameters, comprising: a processor and a communication interface; the communication interface being coupled to the processor for executing a computer program or instructions to implement the method of determining antenna parameters according to any of claims 1-16.
18. A computer readable storage medium having instructions stored therein, characterized in that when executed by a computer, the computer performs the method of determining the antenna parameters of any of the preceding claims 1-16.
CN202211137608.XA 2022-09-19 2022-09-19 Method and device for determining antenna parameters Pending CN117729560A (en)

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CN111148111B (en) * 2019-12-31 2023-02-28 中国移动通信集团江苏有限公司 Method, device and equipment for adjusting antenna parameters and computer storage medium
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