CN113891337A - Deployment position determining method, device and storage medium - Google Patents
Deployment position determining method, device and storage medium Download PDFInfo
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- H04W16/18—Network planning tools
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/22—Traffic simulation tools or models
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Abstract
The application provides a deployment position determining method, a deployment position determining device and a storage medium, relates to the technical field of communication, and is used for solving the technical problem of how to accurately determine a deployment position. The method comprises the following steps: after acquiring a plurality of positions meeting a preset condition in a target area and service data corresponding to service states of a plurality of candidate base stations deployed at the plurality of positions, at least one candidate position may be determined based on the service data of the plurality of candidate base stations, and a target position for deploying the target base station may be determined based on position information of the at least one candidate position and a preset algorithm. The deployment position of the base station which communicates based on the 5G millimeter wave can be accurately determined.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a deployment location determining method, device, and storage medium.
Background
In the fifth generation mobile communication technology (5G), 5G millimeter waves have abundant frequency resources, and have the outstanding advantages of high bandwidth, low delay, and the like.
At present, 5G millimeter waves are still in an experimental stage, and the deployment position of a base station for communication based on the 5G millimeter waves cannot be reasonably determined
Disclosure of Invention
The application provides a deployment location determination method, a deployment location determination device and a storage medium, which are used for solving the problem of how to accurately determine a deployment location.
In order to achieve the purpose, the technical scheme is as follows:
in a first aspect, a deployment location determination method is provided, including: after acquiring a plurality of positions in a target area that satisfy preset conditions (the number of terminals is greater than a preset number, the communication traffic is greater than a preset traffic, and the propagation loss is less than a preset loss) and service data of a plurality of candidate base stations deployed at the plurality of positions, since the service data is used to represent service states of the candidate base stations corresponding to the service data, at least one candidate position may be determined based on the service data of the plurality of candidate base stations, and a target position for deploying the target base station may be determined based on position information of the at least one candidate position and a preset algorithm.
Optionally, the method for determining at least one candidate position based on service data of multiple candidate base stations specifically includes: carrying out normalization processing on the service data; the normalization processing is used for converting the data format of the service data into a target format; determining deployment capacity values of a plurality of candidate base stations based on the service data after normalization processing; selecting at least one candidate base station with the deployment capacity value larger than or equal to a first preset value from the deployment capacity values of the candidate base stations; determining a deployment location of at least one candidate base station as at least one candidate location.
Optionally, the method for determining the target location for deploying the target base station based on the location information of the at least one candidate location and a preset algorithm specifically includes: determining a kernel density for the at least one candidate location based on the location information for the at least one candidate location and a kernel density algorithm; and selecting the candidate position with the kernel density larger than or equal to a second preset value from the kernel densities of at least one candidate position to be determined as the target position.
Optionally, the service data includes: the method comprises the steps of total traffic data flow, total number of access terminals, total business income, total business times, the number of terminals with business flow larger than preset traffic, the number of terminals with monthly average consumption level larger than preset consumption level, the number of terminals of a preset model and the number of terminals to be converted into a fifth generation mobile communication technology 5G terminal.
In a second aspect, a deployment position determining apparatus is provided, comprising: an acquisition unit and a processing unit; the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring a plurality of positions meeting preset conditions in a target area; the preset conditions include one or more of the following: the number of the terminals is larger than the preset number, the communication traffic is larger than the preset traffic, and the propagation loss is smaller than the preset loss; the acquiring unit is further used for acquiring service data of a plurality of candidate base stations deployed at a plurality of positions; the service data is used for representing the service state of the candidate base station corresponding to the service data; the processing unit is used for determining at least one candidate position based on the service data of the candidate base stations acquired by the acquisition unit; and the processing unit is further used for determining a target position for deploying the target base station based on the position information of the at least one candidate position and a preset algorithm.
Optionally, the processing unit is specifically configured to: carrying out normalization processing on the service data; the normalization processing is used for converting the data format of the service data into a target format; determining deployment capacity values of a plurality of candidate base stations based on the service data after normalization processing; selecting at least one candidate base station with the deployment capacity value larger than or equal to a first preset value from the deployment capacity values of the candidate base stations; determining a deployment location of at least one candidate base station as at least one candidate location.
Optionally, the processing unit is specifically configured to: determining a kernel density for the at least one candidate location based on the location information for the at least one candidate location and a kernel density algorithm; and selecting the candidate position with the kernel density larger than or equal to a second preset value from the kernel densities of at least one candidate position to be determined as the target position.
Optionally, the service data includes: the method comprises the steps of total traffic data flow, total number of access terminals, total business income, total business times, the number of terminals with business flow larger than preset traffic, the number of terminals with monthly average consumption level larger than preset consumption level, the number of terminals of a preset model and the number of terminals to be converted into a fifth generation mobile communication technology 5G terminal.
In a third aspect, a deployment position determining apparatus is provided, comprising a memory and a processor; the memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus; when the deployment position determining apparatus is operating, the processor executes computer-executable instructions stored by the memory to cause the deployment position determining apparatus to perform the deployment position determining method as in the first aspect.
The deployment location determination may be a network device or a part of a device in the network device, such as a system on a chip in the network device. The system on chip is configured to support the network device to implement the functions involved in the first aspect and any one of the possible implementations thereof, for example, to receive, determine, and offload data and/or information involved in the data processing method. The chip system includes a chip and may also include other discrete devices or circuit structures.
In a fourth aspect, there is provided a computer-readable storage medium, wherein the computer-readable storage medium comprises computer-executable instructions which, when executed on a computer, cause the computer to perform the deployment location determination method of the first aspect.
It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with the processor of the deployment position determination device or packaged separately from the processor of the deployment position determination device, which is not limited in this application.
In the present application, the names of the above-mentioned deployment location determining apparatuses do not constitute limitations on the devices or functional modules themselves, which may appear by other names in actual implementations. Insofar as the functions of the respective devices or functional modules are similar to those of the present application, they fall within the scope of the claims of the present application and their equivalents.
These and other aspects of the present application will be more readily apparent from the following description.
The technical scheme provided by the application at least brings the following beneficial effects:
based on any one of the above aspects, in the present application, after acquiring a plurality of locations that satisfy preset conditions (the number of terminals is greater than the preset number, the communication traffic is greater than the preset traffic, and the propagation loss is less than the preset loss, etc.) in a target area, and service data of a plurality of candidate base stations deployed at the plurality of locations, since the service data is used to represent service states of the candidate base stations corresponding to the service data, at least one candidate location may be determined based on the service data of the plurality of candidate base stations, and a target location for deploying the target base station may be determined based on location information of the at least one candidate location and a preset algorithm. Therefore, the target area can be subjected to multi-layer screening, and the target position for deploying the target base station in the target area is determined more accurately.
Drawings
Fig. 1 is a schematic structural diagram of a deployment position determining system according to an embodiment of the present application;
fig. 2 is a schematic hardware structure diagram of a communication device according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of another hardware structure of a communication device according to an embodiment of the present disclosure;
fig. 4 is a first flowchart illustrating a deployment location determining method according to an embodiment of the present application;
fig. 5 is a schematic flowchart illustrating a second method for deploying location determination according to an embodiment of the present application;
fig. 6 is a third schematic flowchart of a deployment position determining method according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a deployment position determining apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first" and "second" are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first" and "second" are not used to limit the quantity and execution order.
Furthermore, the terms "comprising" and "having" in the description of the embodiments and claims of the present application and the drawings are not intended to be exclusive. For example, a process, method, system, article, or apparatus that comprises a list of steps or modules is not limited to only those steps or modules listed, but may include other steps or modules not listed.
As described in the background art, the 5G millimeter waves are still in the experimental stage, and the deployment position of the base station that performs communication based on the 5G millimeter waves cannot be reasonably determined.
In view of the foregoing problems, an embodiment of the present application provides a deployment location determining method, where after a plurality of locations that satisfy preset conditions (the number of terminals is greater than a preset number, the communication traffic is greater than a preset traffic, and the propagation loss is less than a preset loss, etc.) in a target area and service data of a plurality of candidate base stations deployed at the plurality of locations are obtained, since the service data is used to represent service states of the candidate base stations corresponding to the service data, at least one candidate location may be determined based on the service data of the plurality of candidate base stations, and a target location for deploying the target base station may be determined based on location information of the at least one candidate location and a preset algorithm. Therefore, the target area can be subjected to multi-layer screening, and the target position for deploying the target base station in the target area is determined more accurately.
The deployment location determining method is suitable for a deployment location determining system. Fig. 1 shows one configuration of the deployment location determining system 100. As shown in fig. 1, the deployment location determining system 100 includes: the position determining device 101 and the server 102 are deployed. The deployment location determining means 101 is communicatively connected to the server 102.
Alternatively, the deployment position determining apparatus 101 in fig. 1 may be an electronic device (e.g., a server or a terminal) for determining a target position for deploying the target base station in the target area.
Alternatively, when the deployment position determining apparatus 101 is a server, the server may be a single server, or may be a server cluster formed by a plurality of servers. In some embodiments, the server cluster may also be a distributed cluster. The embodiments of the present application do not set any limit to this.
Optionally, when the deployment location determining apparatus 101 is a terminal, the terminal is a device providing voice and/or data connectivity to a user, a handheld device having wireless connection capability, or other processing device connected to a wireless modem. A wireless terminal may communicate with one or more core networks via a Radio Access Network (RAN). The wireless terminal may be a mobile terminal, such as a computer having a mobile terminal, or a portable, pocket, hand-held, computer-embedded mobile device, which exchanges language and/or data with a radio access network, for example, a mobile phone, a tablet computer, a notebook computer, a netbook, a Personal Digital Assistant (PDA). The embodiments of the present application do not set any limit to this.
The server 102 is configured to collect and provide the deployment position determining apparatus 101 with position information of all positions in the target area and information such as service data of base stations deployed at all positions.
Alternatively, the server 102 may be a single server, or may be a server cluster composed of a plurality of servers. In some embodiments, the server cluster may also be a distributed cluster. The embodiments of the present application do not set any limit to this.
Alternatively, when the deployment position determining apparatus 101 is a server, the deployment position determining apparatus 101 may be a server provided separately from the server 102, or may be a functional module inside the server 102.
For ease of understanding, the present application is described mainly by taking an example in which the deployment location determining apparatus 101 and the server 102 are independently provided.
It is easily understood that when the deployment position determining apparatus 101 is a functional module inside the server 102, the communication manner between the deployment position determining apparatus 101 and the server 102 is communication between the modules inside the server. In this case, the communication flow between the two is the same as "the communication flow between the deployment position determining apparatus 101 and the server 102 in the case where they are independent from each other".
The deployment position determining apparatus 101 and the server 102 in the deployment position determining system 100 are similar in basic hardware structure and include elements included in the communication apparatus shown in fig. 2 or fig. 3. The hardware configuration of the deployment position determining apparatus 101 and the server 102 will be described below by taking the communication apparatus shown in fig. 2 and 3 as an example.
Fig. 2 is a schematic diagram of a hardware structure of a communication device according to an embodiment of the present disclosure. The communication device comprises a processor 21, a memory 22, a communication interface 23, a bus 24. The processor 21, the memory 22 and the communication interface 23 may be connected by a bus 24.
The processor 21 is a control center of the communication apparatus, and may be a single processor or a collective term for a plurality of processing elements. For example, the processor 21 may be a Central Processing Unit (CPU), other general-purpose processors, or the like. Wherein a general purpose processor may be a microprocessor or any conventional processor or the like.
For one embodiment, processor 21 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 2.
The memory 22 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that may store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that may store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In a possible implementation, the memory 22 may exist separately from the processor 21, and the memory 22 may be connected to the processor 21 via a bus 24 for storing instructions or program codes. The deployment location determining method provided by the embodiments described below of the present application can be implemented by the processor 21 when it calls and executes instructions or program code stored in the memory 22.
In the embodiment of the present application, the software programs stored in the memory 22 are different for the deployment position determination device 101 and the server 102, so the functions implemented by the deployment position determination device 101 and the server 102 are different. The functions performed by the devices will be described in connection with the following flow charts.
In another possible implementation, the memory 22 may also be integrated with the processor 21.
The communication interface 23 is used for connecting the communication device with other devices through a communication network, which may be an ethernet, a radio access network, a Wireless Local Area Network (WLAN), or the like. The communication interface 23 may include a receiving unit for receiving data, and a transmitting unit for transmitting data.
The bus 24 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an extended ISA (enhanced industry standard architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 2, but it is not intended that there be only one bus or one type of bus.
It is noted that the configuration shown in fig. 2 does not constitute a limitation of the communication device, which may comprise more or less components than those shown in fig. 2, or a combination of some components, or a different arrangement of components than those shown in fig. 2.
Fig. 3 shows another hardware configuration of the communication apparatus in the embodiment of the present application. As shown in fig. 3, the communication device may include a processor 31 and a communication interface 32. The processor 31 is coupled to a communication interface 32.
The function of the processor 31 may refer to the description of the processor 21 above. The processor 31 also has a memory function and can function as the memory 22.
The communication interface 32 is used to provide data to the processor 31. The communication interface 32 may be an internal interface of the communication device, or may be an external interface (corresponding to the communication interface 23) of the communication device.
It is noted that the configuration shown in fig. 2 (or fig. 3) does not constitute a limitation of the communication apparatus, which may include more or less components than those shown in fig. 2 (or fig. 3), or combine some components, or a different arrangement of components, in addition to the components shown in fig. 2 (or fig. 3).
Fig. 4 is a schematic flow chart of a deployment position determining method according to an embodiment of the present application. The deployment position determining method is applied to a deployment position determining device belonging to a deployment position determining system composed of the deployment position determining device shown in fig. 1 and a server. The deployment location determining method includes: S401-S404.
S401, the deployment position determining device obtains a plurality of positions meeting preset conditions in the target area.
Specifically, when a 5G millimeter wave needs to be deployed on a 5G base station in the target area, the deployment position determining device may obtain a plurality of positions that satisfy the preset condition in the target area.
Wherein the preset conditions include one or more of the following: the number of terminals is greater than the preset number, the communication traffic is greater than the preset traffic, and the propagation loss is less than the preset loss.
Alternatively, the target area may be a geographical area represented by a name of a place, or a geographical range represented by latitude and longitude. The embodiments of the present application do not limit this.
Optionally, the plurality of positions that satisfy the plurality of preset conditions (that is, the number of terminals is greater than the preset number, the communication traffic is greater than the preset traffic, and the propagation loss is less than the preset loss) may be scenes such as a dense business area, a dense residential area, a campus, a large cultural relic venue, a large square, and a transportation hub in the target area.
It should be noted that when the preset condition is that the number of terminals is greater than the preset number, according to a definition in a Technical Report (TR) of the 3rd generation partnership project (3 GPP), it may be determined that the scenarios related to the high frequency band (6-15GHz) application are indoor hot spots, dense urban areas, macro coverage, high speed railway access and backhaul, and satellite extension to the ground. In these scenarios, the number of terminals is generally greater than the preset number.
When the preset condition is that the propagation loss is smaller than the preset loss, the outdoor scene and the indoor scene can be screened according to the main reason causing the propagation loss. The main causes of propagation loss are: a. causing multiple reflections and diffractions. Due to the influence of reflection and diffraction, under the same transceiver distance condition, extra LOSs of about 10-20 decibels (dB) may exist in non-line of sight (NLOS) propagation compared with line of sight (LOS) propagation; b. there is a tree shadowing condition. For outdoor coverage of urban areas, although there is no forest scene with large loss, the greening vegetation also brings propagation loss; c. the average number of rainfall per month is more than the preset number. For a part of millimeter wave frequency bands, although the atmospheric absorption influence can be ignored, in rainy areas, the rain attenuation needs to be considered in an important way.
Therefore, in order to meet the requirement that the propagation loss is less than the preset loss, for outdoor scenes, scenes such as streets in dense urban areas and wider squares are generally selected. For an indoor scenario, compared to an outdoor scenario, the communication environment is simpler, the wireless communication distance is generally shorter, and the propagation loss is generally smaller than the preset loss.
When the preset condition is that the communication traffic is greater than the preset traffic, the outdoor scenes of the urban macro cells (Uma) such as macro coverage and satellite expansion to the ground can be excluded from the scene categories meeting the condition that the number of terminals is greater than the preset number. This is because the base station spacing of Uma is about 3km, the base station antenna is higher than the roof height, which is a more typical deployment scenario of macro base station, and the communication traffic is generally less than the preset traffic.
Optionally, the server may store information of all locations in the target area, and scene categories (e.g., dense business area, dense residential area, campus, large cultural relic venue, etc.) corresponding to all the locations one to one. When a plurality of positions satisfying a preset condition in the target area need to be acquired, the deployment position determining device may determine a plurality of scene categories according to the preset condition, and send a request message for acquiring the plurality of positions corresponding to the plurality of scene categories to the server. The server may read a plurality of locations corresponding to the plurality of scene categories and transmit the plurality of locations corresponding to the plurality of scene categories to the deployment location determining device in response to a request message for acquiring the plurality of locations corresponding to the plurality of scene categories. Accordingly, the deployment location determining apparatus receives information of a plurality of locations corresponding to a plurality of scene categories from the server.
S402, the deployment position determining device obtains service data of a plurality of candidate base stations deployed at a plurality of positions.
Specifically, after acquiring a plurality of positions that satisfy the preset condition in the target area, the deployment position determining apparatus may acquire service data of a plurality of candidate base stations deployed at the plurality of positions.
The service data is used for representing the service state of the candidate base station corresponding to the service data.
The service data may include a total traffic flow (for example, a total traffic flow generated by the service data on the candidate base station is 1000 mega (M)), a total number of access terminals (for example, 500 terminals are accessed by the candidate base station in total), a total revenue of the service (for example, 50 ten thousand RMB revenue is generated by all services within a coverage area of the candidate base station in total), a total number of the service (for example, 10000 services are generated by the candidate base station in total), a number of terminals whose traffic flow is greater than a preset traffic flow (for example, the preset traffic flow may be 20G, 200 terminals whose traffic flow is greater than 20G are accessed in total), a number of terminals whose monthly average consumption level is greater than a preset consumption level (for example, the preset consumption level may be 100 yuan/month, terminals whose monthly average consumption level is greater than 100 yuan/month are accessed in total), a number of terminals of preset models (for example, the preset models may be a high-end model A and a high-end model B, if the candidate base station has access to 200 terminals of the high-end model a, 100 terminals of the high-end model B, and 200 terminals of the low-end model C, 300 terminals of the preset model are accessed in total), and the number of terminals to be converted into 5G terminals (for example, the candidate base station has access to 100 terminals to be converted into 5G terminals in total).
Optionally, the manner in which the deployment position determining apparatus obtains the service data of the multiple candidate base stations deployed at multiple positions may refer to the manner in which the deployment position determining apparatus obtains multiple positions meeting the preset condition in the target area in S401, and is not described herein again.
For example, the preset deployment position determining device may obtain service data of the candidate base station a deployed at the position a, service data of the candidate base station B deployed at the position B, and service data of the candidate base station C deployed at the position C from the server when obtaining the three positions A, B and C meeting the preset condition in the target area. a. And b, after acquiring service data such as total flow, total user number, total income, total service times, large flow user number, high-value user number, high-consumption user number, potential 5G user number and the like, the three candidate base stations can send the service data to a server. Correspondingly, the server can receive and store the service data collected by the three candidate base stations a, b and c.
S403, the deployment position determining device determines at least one candidate position based on the service data of the candidate base stations.
Specifically, after acquiring the service data of the plurality of candidate base stations deployed at the plurality of positions, the deployment position determining apparatus may determine at least one candidate position based on the service data of the plurality of candidate base stations.
Optionally, the deployment position determining apparatus determines at least one candidate position based on the service data of the plurality of candidate base stations, which includes but is not limited to the following two manners.
The first mode is as follows:
the deployment position determining device may perform data normalization on the traffic data of each candidate base station according to a min-max normalization method, then obtain a sum of all data in the traffic data of each candidate base station, select at least one sum greater than a preset threshold from the obtained plurality of sums in one-to-one correspondence with the traffic data of the plurality of candidate base stations, and determine at least one position where the at least one candidate base station corresponding to the at least one sum greater than the preset threshold is located as the at least one candidate position.
The second mode is as follows:
the deployment position determining apparatus may perform data normalization on the traffic data of each candidate base station according to a z-score normalization method, then find a sum of all data in the traffic data of each candidate base station, select at least one sum greater than a preset threshold from the found plurality of sums corresponding to the traffic data of the plurality of candidate base stations one to one, and determine at least one position where the at least one candidate base station corresponding to the at least one sum greater than the preset threshold is located as the at least one candidate position.
S404, the deployment position determining device determines a target position for deploying the target base station based on the position information of the at least one candidate position and a preset algorithm.
Specifically, after determining the at least one candidate location, the deployment location determining apparatus may determine the target location for deploying the target base station based on the location information of the at least one candidate location and a preset algorithm.
Alternatively, the preset algorithm may be a kernel density estimation algorithm.
It is understood that the 5G base station deployed at the target location may be a target 5G base station deployed in the target area by the 5G millimeter wave.
Alternatively, the deployment position determining apparatus determines the target position for deploying the target base station based on the position information of the at least one candidate position and a preset algorithm, which may include, but is not limited to, the following two ways.
The first mode is as follows:
when the kernel density estimation algorithm is based on a gaussian kernel function, the deployment position determining device may determine a kernel function through the gaussian kernel function and the position information of each candidate position to obtain at least one kernel function corresponding to at least one candidate position, and then linearly superimpose the at least one kernel function to obtain a kernel density function, thereby obtaining a kernel density value of the at least one candidate position according to the kernel density function, and determining a candidate position in the at least one candidate position, in which the kernel density value is greater than a preset kernel density value, as the target position.
The second mode is as follows:
when the kernel density estimation algorithm is based on a uniform kernel function, the deployment position determining device may determine a kernel function through the uniform kernel function and the position information of each candidate position to obtain at least one kernel function corresponding to at least one candidate position, and then linearly superimpose the at least one kernel function to obtain a kernel density function, thereby obtaining a kernel density value of the at least one candidate position according to the kernel density function, and determining a candidate position in the at least one candidate position, in which the kernel density value is greater than a preset kernel density value, as the target position.
In an implementable manner, referring to fig. 4 and as shown in fig. 5, in S403, the method for determining at least one candidate location by the deployment location determining apparatus based on the service data of the multiple candidate base stations specifically includes: S501-S504.
S501, the deployment position determining device performs normalization processing on the service data.
Specifically, after acquiring the service data of the candidate base stations deployed at the multiple positions, the deployment position determining apparatus may perform normalization processing on the service data.
The normalization processing is used for converting the data format of the service data into a target format.
Optionally, when the service data includes data of 8 dimensions, which is total traffic, total number of users, total revenue, total number of services, number of large-traffic users, number of high-value users, number of high-consumption users, and potential number of 5G users, the data of 8 dimensions may be normalized according to the first formula because units of the data of 8 dimensions are different. The first formula is:
wherein n is one of 8 positive integers of 1,2, … and 8,
for normalizing the processed data of the nth dimension, anIs data of the nth dimension, aminIs the value of the data with the smallest absolute value among the data of 8 dimensions,amaxthe value of the data having the largest absolute value among the data of 8 dimensions.
S502, the deployment position determining device determines deployment capacity values of the candidate base stations based on the service data after normalization processing.
Specifically, after the normalization processing is performed on the service data, the deployment position determining device may determine the deployment capability values of the plurality of candidate base stations based on the service data after the normalization processing.
Optionally, the deployment position determining apparatus may input all data in the normalized service data into the second formula, and determine the deployment capability values of the multiple candidate base stations. The second formula is:
wherein n is a positive integer greater than zero, w is a deployment capability value of a candidate base station,
is the data of the nth dimension in the normalized service data, wnIs the weight coefficient of the nth dimension data.
Note that the weight coefficient w1，w2，…，wnThe sum of (1) represents the importance of each dimension, which can be preset by a human operator empirically.
S503, the deployment position determining device selects at least one candidate base station with the deployment capability value larger than or equal to a first preset value from the deployment capability values of the candidate base stations.
Specifically, after determining the deployment capability values of the plurality of candidate base stations, the deployment position determining apparatus may select at least one candidate base station whose deployment capability value is greater than or equal to a first preset value from the deployment capability values of the plurality of candidate base stations.
Optionally, the first preset value may be determined according to one of the deployment capability values of the candidate base stations, or may be manually and empirically determined. The embodiments of the present application do not limit this.
S504, the deployment position determining device determines the deployment position of at least one candidate base station as at least one candidate position.
Specifically, after selecting at least one candidate base station whose deployment capability value is greater than or equal to the first preset value, the deployment position determining device may determine the deployment position of the at least one candidate base station as the at least one candidate position.
Illustratively, the deployment capability value of the candidate base station a is preset to be 0.3, the deployment capability value of the candidate base station B is preset to be 0.6, and the deployment capability value of the candidate base station C is preset to be 0.8. The first predetermined value may be 0.5, determined empirically by a human. The deployment position determining means selects the candidate base stations B and C having the deployment capability values larger than 0.5 from the deployment capability values of the candidate base stations A, B and C, and determines the deployment positions of the candidate base stations B and C as candidate positions.
In an implementation manner, referring to fig. 4 and as shown in fig. 6, in the above S404, the method for determining a target location for deploying the target base station by the deployment location determining apparatus based on the location information of the at least one candidate location and a preset algorithm specifically includes: S601-S602.
S601, the deployment position determining device determines the kernel density of at least one candidate position based on the position information of the at least one candidate position and a kernel density algorithm.
Specifically, after determining the at least one candidate location, the deployment location determining apparatus may determine the kernel density of the at least one candidate location based on the location information of the at least one candidate location and a kernel density algorithm.
Optionally, the location information of the at least one candidate location may be latitude and longitude information of the at least one candidate location.
Optionally, when the kernel density algorithm is based on a gaussian kernel function, the deployment position determining device may respectively calculate the kernel density of the at least one candidate position according to the longitude and latitude distribution of the at least one candidate position, that is, a two-dimensional gaussian kernel density estimation value.
For example, if the longitude and latitude information of one candidate location x is preset as x ═ lon, lat ], the kernel density function representing one candidate location x may be:
where n is the total number of all candidate locations, lon is the longitude of the candidate location x, lat is the latitude of the candidate location x, loniFor the longitude, lat, of the candidate position x after screeningiFor the latitude, K, of the candidate position x after screening0(. cndot.) is a Gaussian kernel function. h is a smoothing parameter in the kernel density estimation algorithm.
It should be noted that the initial value of h is usually set to a value greater than 0. Subsequently, the value of h can be adjusted through a kernel density estimation algorithm based on a Gaussian kernel function, so that the kernel density of the candidate position can be accurately determined.
The formula of the gaussian kernel function is:
h needs to be selected after the Gaussian kernel function is selected, the smoothing parameter h is corrected by adopting a kernel density estimation method, and the kernel density function of the target area is obtained as follows:
wherein n is a positive integer greater than zero, i is a positive integer greater than zero and less than or equal to n, hiA smoothing parameter h for the ith candidate position, f (x) a bandwidth hiN is the total number of all candidate locations, K0(. cndot.) is a kernel function. Alpha is a sensitivity factor for correctionThe smoothing parameter has a value range of 0-1, usually 0.5.
S602, the deployment position determining device selects a candidate position with the nuclear density larger than or equal to a second preset value from the nuclear density of at least one candidate position to determine as a target position.
Specifically, after determining the kernel density of the at least one candidate location, the deployment location determining apparatus may select, from the kernel densities of the at least one candidate location, a candidate location having a kernel density greater than or equal to a second preset value to determine as the target location.
Optionally, the second preset value may be determined according to one of the kernel densities of the at least one candidate location, or may be manually and empirically determined. The embodiments of the present application do not limit this.
Illustratively, the pre-set calculation results in that the kernel density of the candidate position a is a, the kernel density of the candidate position B is 2a, and the kernel density of the candidate position C is 3 a. The second predetermined value may be 3a to select the candidate position with the highest kernel density. The deployment position determining means may select a C candidate position equal to a second preset value (i.e., 3a) from the core densities of the A, B and the C candidate positions to determine as the target position.
In the embodiment of the application, after acquiring a plurality of positions in a target area that satisfy preset conditions (the number of terminals is greater than the preset number, the communication traffic is greater than the preset traffic, and the propagation loss is less than the preset loss, etc.) and service data of a plurality of candidate base stations deployed at the plurality of positions, since the service data is used for representing service states of the candidate base stations corresponding to the service data, at least one candidate position may be determined based on the service data of the plurality of candidate base stations, and a target position for deploying the target base station may be determined based on position information of the at least one candidate position and a preset algorithm. Therefore, the target area can be subjected to multi-layer screening, and the target position for deploying the target base station in the target area is determined more accurately.
The scheme provided by the embodiment of the application is mainly introduced from the perspective of a method. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art would readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the terminal may be divided into the functional modules according to the method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. Optionally, the division of the modules in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Fig. 7 is a schematic structural diagram of a deployment position determining apparatus according to an embodiment of the present application. The deployment location determining apparatus may be used to perform the deployment location determining method as shown in fig. 4 to 6. The deployment position determining apparatus shown in fig. 6 includes: an acquisition unit 701 and a processing unit 702.
An obtaining unit 701 is configured to obtain a plurality of positions in the target area that satisfy a preset condition. The preset conditions include one or more of the following: the number of terminals is greater than the preset number, the communication traffic is greater than the preset traffic, and the propagation loss is less than the preset loss. For example, in conjunction with fig. 4, the acquisition unit 701 may be configured to perform S401.
The obtaining unit 701 is further configured to obtain service data of a plurality of candidate base stations deployed at a plurality of positions. The service data is used for representing the service state of the candidate base station corresponding to the service data. For example, in conjunction with fig. 4, the obtaining unit 701 may be configured to perform S402.
A processing unit 702, configured to determine at least one candidate position based on the service data of the multiple candidate base stations acquired by the acquiring unit 701. For example, in conjunction with fig. 4, the acquisition unit 701 may be configured to perform S403.
The processing unit 702 is further configured to determine a target location for deploying the target base station based on the location information of the at least one candidate location and a preset algorithm. For example, in conjunction with fig. 4, the obtaining unit 701 may be configured to perform S404.
Optionally, the processing unit 702 is specifically configured to:
carrying out normalization processing on the service data; the normalization process is used for converting the data format of the service data into a target format. For example, in conjunction with fig. 5, the processing unit 702 may be configured to perform S501.
And determining the deployment capacity values of the candidate base stations based on the service data after the normalization processing. For example, in conjunction with fig. 5, the processing unit 702 may be configured to perform S502.
Selecting at least one candidate base station with the deployment capability value larger than or equal to a first preset value from the deployment capability values of the candidate base stations. For example, in conjunction with fig. 5, the processing unit 702 may be configured to execute S503.
Determining a deployment location of at least one candidate base station as at least one candidate location. For example, in conjunction with fig. 5, the processing unit 702 may be configured to perform S504.
Optionally, the processing unit 702 is specifically configured to:
a kernel density for the at least one candidate location is determined based on the location information for the at least one candidate location and a kernel density algorithm. For example, in connection with fig. 6, the processing unit 702 may be configured to execute S601.
And selecting the candidate position with the kernel density larger than or equal to a second preset value from the kernel densities of at least one candidate position to be determined as the target position. For example, in conjunction with fig. 6, the processing unit 702 may be configured to perform S602.
Optionally, the service data includes: the method comprises the steps of total traffic data flow, total number of access terminals, total business income, total business times, the number of terminals with business flow larger than preset traffic, the number of terminals with monthly average consumption level larger than preset consumption level, the number of terminals of a preset model and the number of terminals to be converted into a fifth generation mobile communication technology 5G terminal.
Those skilled in the art will recognize that in one or more of the examples described above, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer-readable storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules or units is only one logical function division, and there may be other division ways in actual implementation. For example, various elements or components may be combined or may be integrated into another device, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for deployment location determination, comprising:
acquiring a plurality of positions meeting preset conditions in a target area; the preset conditions include one or more of the following: the number of the terminals is larger than the preset number, the communication traffic is larger than the preset traffic, and the propagation loss is smaller than the preset loss;
acquiring service data of a plurality of candidate base stations deployed at the plurality of positions; the service data is used for representing the service state of the candidate base station corresponding to the service data;
determining at least one candidate position based on traffic data of the plurality of candidate base stations;
and determining a target position for deploying the target base station based on the position information of the at least one candidate position and a preset algorithm.
2. The method of claim 1, wherein determining at least one candidate location based on the traffic data of the candidate base stations comprises:
carrying out normalization processing on the service data; the normalization processing is used for converting the data format of the service data into a target format;
determining deployment capacity values of the candidate base stations based on the service data after normalization processing;
selecting at least one candidate base station with the deployment capability value larger than or equal to a first preset value from the deployment capability values of the candidate base stations;
determining a deployment location of the at least one candidate base station as the at least one candidate location.
3. The method according to claim 1, wherein the determining the target location for deploying the target base station based on the location information of the at least one candidate location and a preset algorithm comprises:
determining a kernel density for the at least one candidate location based on the location information for the at least one candidate location and a kernel density algorithm;
and selecting a candidate position with the kernel density larger than or equal to a second preset value from the kernel densities of the at least one candidate position to be determined as the target position.
4. The deployment location determining method of claim 1, wherein the traffic data comprises: the method comprises the steps of total traffic data flow, total number of access terminals, total business income, total business times, the number of terminals with business flow larger than preset traffic, the number of terminals with monthly average consumption level larger than preset consumption level, the number of terminals of a preset model and the number of terminals to be converted into a fifth generation mobile communication technology 5G terminal.
5. A deployment location determining apparatus, comprising: an acquisition unit and a processing unit;
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring a plurality of positions meeting preset conditions in a target area; the preset conditions include one or more of the following: the number of the terminals is larger than the preset number, the communication traffic is larger than the preset traffic, and the propagation loss is smaller than the preset loss;
the acquiring unit is further configured to acquire service data of a plurality of candidate base stations deployed at the plurality of positions; the service data is used for representing the service state of the candidate base station corresponding to the service data;
the processing unit is used for determining at least one candidate position based on the service data of the candidate base stations acquired by the acquiring unit;
and the processing unit is further used for determining a target position for deploying the target base station based on the position information of the at least one candidate position and a preset algorithm.
6. The deployment position determining apparatus of claim 5, wherein the processing unit is specifically configured to:
carrying out normalization processing on the service data; the normalization processing is used for converting the data format of the service data into a target format;
determining deployment capacity values of the candidate base stations based on the service data after normalization processing;
selecting at least one candidate base station with the deployment capability value larger than or equal to a first preset value from the deployment capability values of the candidate base stations;
determining a deployment location of the at least one candidate base station as the at least one candidate location.
7. The deployment position determining apparatus of claim 5, wherein the processing unit is specifically configured to:
determining a kernel density for the at least one candidate location based on the location information for the at least one candidate location and a kernel density algorithm;
and selecting a candidate position with the kernel density larger than or equal to a second preset value from the kernel densities of the at least one candidate position to be determined as the target position.
8. The deployment location determining apparatus of claim 5, wherein the traffic data comprises: the method comprises the steps of total traffic data flow, total number of access terminals, total business income, total business times, the number of terminals with business flow larger than preset traffic, the number of terminals with monthly average consumption level larger than preset consumption level, the number of terminals of a preset model and the number of terminals to be converted into a fifth generation mobile communication technology 5G terminal.
9. A deployment position determining apparatus comprising a memory and a processor; the memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus; the processor executes the computer-executable instructions stored by the memory when the deployment position determination device is operating to cause the deployment position determination device to perform the deployment position determination method of any of claims 1-4.
10. A computer-readable storage medium comprising computer-executable instructions that, when executed on a computer, cause the computer to perform the deployment location determination method of any of claims 1-4.
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