CN114980135B - 5G base station site distribution system and method based on big data - Google Patents
5G base station site distribution system and method based on big data Download PDFInfo
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Abstract
The invention provides a 5G base station site distribution system and a method based on big data, wherein the system comprises the following steps: the acquisition module is used for acquiring first area information of a first area needing to be subjected to 5G base station address distribution; the formulating module is used for formulating a base station arrangement strategy suitable for the first area according to the first area information based on big data technology; and the execution module is used for scheduling a plurality of first staff to perform corresponding base station arrangement in the first area according to the base station arrangement strategy, and completing the 5G base station site arrangement after the base station arrangement is completed. According to the 5G base station address distribution system and method based on big data, the proper arrangement strategy is determined based on the first area information of 5G base station address distribution based on the big data technology, and corresponding arrangement is performed, so that the rationality of the arrangement strategy is improved.
Description
Technical Field
The invention relates to the field of big data analysis, in particular to a 5G base station site distribution system and method based on big data.
Background
At present, 5G communication services are rapidly developed, coverage of a related communication network is rapidly increased (for example, because more base stations are needed for building a 5G communication network compared with 4G network communication), a 5G base station is used as key equipment of the 5G communication network, the layout of the 5G base station directly influences quality of regional signals, the existing base station layout is generally designed by manually performing layout strategies (for example, engineering designers perform targeted design through own experience and site information), and under the condition that the engineering designers rely on experience, consideration factors are easily caused to be incomplete, and base station layout is unreasonable.
Thus, a solution is needed.
Disclosure of Invention
The invention aims to provide a 5G base station address distribution system and method based on big data, which are used for determining a proper arrangement strategy based on a big data technology based on first area information of 5G base station address distribution and carrying out corresponding arrangement, so that the rationality of the arrangement strategy is improved.
The 5G base station site distribution system based on big data provided by the embodiment of the invention comprises:
the acquisition module is used for acquiring first area information of a first area needing to be subjected to 5G base station address distribution;
the formulating module is used for formulating a base station arrangement strategy of the first area according to the first area information based on big data technology;
and the execution module is used for scheduling a plurality of first staff to perform base station arrangement in the first area according to the base station arrangement strategy, and completing the 5G base station site arrangement after the base station arrangement is completed.
Preferably, the formulation module performs the following operations:
based on a big data technology, acquiring a plurality of first arrangement processes for manually performing 5G base station site arrangement;
verifying the availability of the first arrangement process, and taking the verified first arrangement process as a second arrangement process;
Based on a preset model training algorithm, performing model training according to all the second arrangement processes to obtain a base station arrangement strategy making model;
and formulating a base station arrangement strategy of the first area according to the first area information based on the base station arrangement strategy formulation model.
Preferably, verifying the availability of the first arrangement procedure includes:
acquiring second area information of a second area correspondingly arranged in the first arrangement process;
extracting the characteristics of the first region information to obtain a plurality of first information characteristics;
extracting the characteristics of the second region information to obtain a plurality of second information characteristics;
performing feature matching on the first information feature and the second information feature to obtain a matching value matched with the first information feature;
if the matching value is greater than or equal to a preset matching value threshold, acquiring a first information type corresponding to the first information feature or the second information feature to be matched, and associating the corresponding matching value with the first information type;
accumulating and calculating the matching value associated with the first information type to obtain a matching value sum;
if the matching value sum is greater than or equal to a preset matching value and a threshold value corresponding to the first information type, the corresponding first information type is used as a second information type;
Inquiring a preset information type-criticality library, and determining the criticality of the second information type;
accumulating and calculating the criticality corresponding to each second information type, obtaining a criticality sum, and correlating with the corresponding first arrangement process;
acquiring at least one 5G base station communication abnormal event which occurs historically in the second area;
based on a preset causality analysis model, analyzing causality between the first arrangement process and the communication abnormal event to obtain a causality value;
if the cause and effect value is greater than or equal to a preset cause and effect value threshold, carrying out severity analysis on the communication abnormal event based on a preset severity analysis model, obtaining a severity value, and associating with the corresponding first arrangement process;
accumulating and calculating the criticality and the severity value associated with the first arrangement process to obtain availability;
if the availability is greater than or equal to a preset availability threshold, determining that the corresponding first arrangement process passes verification;
otherwise, it is determined that the verification is not passed.
Preferably, the 5G base station site distribution system based on big data further comprises:
the reminding module is used for acquiring a plurality of first arrangement behaviors generated by the first staff in the first area when the first staff performs base station arrangement in the first area, judging whether the first arrangement behaviors are standard or not, and reminding the first staff if not.
Preferably, the reminding module judges whether the first arrangement behavior is standard, and if not, reminds the first staff, including:
performing behavior specification judgment on the first arrangement behaviors based on a preset behavior specification judgment model to obtain second arrangement behaviors which are judged to be nonstandard behaviors in the first arrangement behaviors, and taking the first staff corresponding to the second arrangement behaviors as second staff;
acquiring the working position of the second staff and the first staff information;
acquiring a preset dynamic display robot distribution diagram;
based on the dynamic display robot distribution diagram, acquiring a dynamic display robot closest to the working position, and controlling the dynamic display robot to go to the working position;
when the dynamic display robot reaches the working position, controlling the dynamic display robot to acquire second personnel information of a third worker within a preset range of the working position;
sequentially traversing the second personnel information, and taking the traversed second personnel information as third personnel information;
matching the first personnel information with the third personnel information, and taking a third staff corresponding to the matched third personnel information as a learner if the matching is met;
Controlling the dynamic display robot to dynamically acquire the sight range of the learner;
analyzing the second arrangement behaviors corresponding to the learner to acquire learning items of the learner;
based on a preset display rule, controlling the dynamic display robot to dynamically display in the sight range according to the learning item;
and when the dynamic display robot finishes displaying, finishing reminding.
Preferably, the 5G base station site distribution system based on big data further comprises:
the simulation module is used for performing simulation test on the 5G base station system based on the base station arrangement strategy before the base station arrangement is performed, and optimizing the base station arrangement strategy based on a test result of the simulation test;
the simulation module performs the following operations:
based on a virtual reference station technology, according to the base station arrangement strategy, setting a simulation base station in the first area to obtain a simulation 5G base station system;
based on a preset test point selection rule, acquiring a plurality of simulation test points in the simulation 5G base station system;
performing analog signal testing on the analog test point to obtain the signal strength of an analog test signal of the analog test point;
Determining a test result of the simulation test according to a preset test result judging rule based on the signal strength of the simulation test signal;
and optimizing based on the test result.
Preferably, optimizing based on the simulation test result includes:
judging whether the 5G base station site distribution system needs to be optimized or not based on the test result;
if the optimization is judged to be needed, acquiring map information of the first area;
based on the map information, a two-dimensional distribution map corresponding to the map information is manufactured;
marking the signal intensity of the analog test signal on the two-dimensional distribution map;
transmitting the two-dimensional distribution diagram after marking to a preset expert node, and analyzing the interference cause of the first area by the expert node;
acquiring at least one first interference cause based on the interference cause analysis;
obtaining an interference type of the first interference cause, wherein the interference type comprises: active interference and passive interference;
when the interference type is active interference, inquiring a preset interference reason-active interference optimization scheme library to obtain at least one second interference reason;
extracting a first interference characteristic of the first interference cause, and simultaneously extracting a second interference characteristic of the second interference cause;
Performing feature matching on the first interference feature and the second interference feature, and if the matching is met, acquiring a third interference feature which is met by the matching;
inquiring a preset interference characteristic-weight value library, determining a weight value of the third interference characteristic, and correlating with the second interference cause;
accumulating and calculating the weight value associated with the second interference cause to obtain a weight value sum;
if the weight value sum is greater than or equal to a preset weight value threshold, taking the corresponding second interference reason as a third interference reason;
determining a first optimization scheme corresponding to the third interference cause based on the interference cause-active interference optimization scheme library;
acquiring a preset effect analysis model, and analyzing the first optimization scheme to obtain a first treatment effect value of the first optimization scheme;
inquiring a preset weight value and adjustment degree library, and determining the adjustment degree of a first processing effect value corresponding to the first optimization scheme based on the weight value sum of a third interference reason corresponding to the first optimization scheme;
determining a second processing effect value corresponding to the first optimization scheme based on the first processing effect value corresponding to the first optimization scheme and the adjustment degree;
Determining a first optimization scheme with the maximum second treatment effect value as a second optimization scheme;
scheduling the first staff member for optimization based on the second optimization scheme;
when the interference type is passive interference, a preset judgment ring is obtained, and the judgment ring is controlled to randomly displace in the two-dimensional distribution diagram;
based on the signal intensity of the analog test signal, judging a third area needing to be optimized in the two-dimensional distribution diagram according to a preset judgment circle judgment rule;
acquiring a complaint log of the user in the third area;
analyzing the complaint log to obtain a complaint piece area of a complaint user corresponding to the two-dimensional distribution map;
notifying a detector closest to the complaint zone to carry detection equipment to the complaint zone;
when the detection personnel reach the complaint piece area, detecting interference equipment in a fourth area of the preset range of the complaint piece area;
detecting the interference equipment in the fourth area based on a preset interference detection rule, and determining the interference equipment in the fourth area;
acquiring an equipment management side of the interference equipment, and coordinating with the equipment management side based on a preset coordination rule;
If the coordination is successful, the optimization is completed;
if coordination fails, a preset base station adjustment strategy library is obtained, and a base station adjustment strategy for the interference equipment is determined based on a third interference reason of the interference equipment;
based on the base station adjustment strategy, adjusting the base station arrangement strategy to obtain an adjusted optimal arrangement strategy;
and scheduling the first staff to conduct 5G base station site distribution in the first area based on the optimal arrangement strategy.
The invention provides a 5G base station site distribution method based on big data, which comprises the following steps:
step S1: acquiring first area information of a first area needing to be subjected to 5G base station address distribution;
step S2: based on big data technology, formulating a base station arrangement strategy of the area according to the first area information;
step S3: and dispatching a plurality of first staff to perform base station arrangement in the first area according to the base station arrangement strategy, and completing 5G base station site arrangement after the base station arrangement is completed.
Preferably, step S2: based on big data technology, according to the first area information, formulating a base station arrangement strategy of the area, including:
based on a big data technology, acquiring a plurality of first arrangement processes for manually performing 5G base station site arrangement;
Verifying the availability of the first arrangement process, and taking the verified first arrangement process as a second arrangement process;
based on a preset model training algorithm, performing model training according to the second arrangement process to obtain a base station arrangement strategy making model;
and formulating a base station arrangement strategy according to the first area information based on the base station arrangement strategy formulation model.
Preferably, verifying the availability of the first arrangement procedure includes:
acquiring second area information of a second area correspondingly arranged in the first arrangement process;
extracting the characteristics of the first region information to obtain a plurality of first information characteristics;
extracting the characteristics of the second region information to obtain a plurality of second information characteristics;
performing feature matching on the first information feature and the second information feature to obtain a matching value matched with the first information feature;
if the matching value is greater than or equal to a preset matching value threshold, acquiring a first information type corresponding to the first information feature or the second information feature to be matched, and associating the corresponding matching value with the first information type;
accumulating and calculating the matching value associated with the first information type to obtain a matching value sum;
If the matching value sum is greater than or equal to a preset matching value and a threshold value corresponding to the first information type, the corresponding first information type is used as a second information type;
inquiring a preset information type-criticality library, and determining the criticality of the second information type;
accumulating and calculating the criticality corresponding to each second information type, obtaining a criticality sum, and correlating with the corresponding first arrangement process;
acquiring at least one 5G base station communication abnormal event which occurs historically in the second area;
based on a preset causality analysis model, analyzing causality between the first arrangement process and the communication abnormal event to obtain a causality value;
if the cause and effect value is greater than or equal to a preset cause and effect value threshold, carrying out severity analysis on the communication abnormal event based on a preset severity analysis model, obtaining a severity value, and associating with the corresponding first arrangement process;
accumulating and calculating the criticality and the severity value associated with the first arrangement process to obtain availability;
if the availability is greater than or equal to a preset availability threshold, determining that the corresponding first arrangement process passes verification;
Otherwise, it is determined that the verification is not passed.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic diagram of a 5G base station address distribution method based on big data in an embodiment of the present invention;
fig. 2 is a flowchart of a 5G base station address distribution method based on big data in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a 5G base station site distribution system based on big data, as shown in fig. 1, comprising:
The acquisition module 1 is used for acquiring first area information of a first area needing to be subjected to 5G base station address distribution;
a formulation module 2, configured to formulate a base station arrangement policy of the first area according to the first area information based on a big data technology;
and the execution module 3 is used for scheduling a plurality of first staff to perform base station arrangement in the first area according to the base station arrangement strategy, and completing the 5G base station site arrangement after the base station arrangement is completed.
The working principle and the beneficial effects of the technical scheme are as follows:
acquiring first area information (such as topographic information, cell distribution, population density and the like of a first area needing to be subjected to 5G base station arrangement), determining a proper base station arrangement strategy according to the first area information based on a big data technology, and carrying out corresponding base station arrangement in the first area based on the base station arrangement strategy, wherein after the base station arrangement needing to be subjected to arrangement is completed, the base station arrangement is completed;
the embodiment of the invention determines the proper arrangement strategy based on the big data technology based on the first area information of the 5G base station address distribution, and carries out corresponding arrangement, thereby improving the rationality and the comprehensiveness of the arrangement strategy.
The 5G base station site distribution system based on big data provided by the embodiment of the invention, the making module 2 executes the following operations:
based on a big data technology, acquiring a plurality of first arrangement processes for manually performing 5G base station site arrangement;
verifying the availability of the first arrangement process, and taking the verified first arrangement process as a second arrangement process;
based on a preset model training algorithm, performing model training according to the second arrangement process to obtain a base station arrangement strategy making model;
and formulating a base station arrangement strategy according to the first area information based on the base station arrangement strategy formulation model.
The working principle and the beneficial effects of the technical scheme are as follows:
when the base station arrangement strategy making model is trained, a plurality of first arrangement processes can be obtained through big data, but not all the first arrangement processes have high referenceability, and if the referenceability of the first arrangement processes is low, the trained base station arrangement strategy making model is unreasonable; therefore, a solution is needed;
the method comprises the steps of obtaining a first arrangement process (manually recorded base station arrangement process obtained based on a big data technology) of a plurality of 5G base station sites, respectively verifying the availability of the first arrangement process, and if the availability of the first arrangement process is verified, performing model training on a second arrangement process passing verification to obtain a base station arrangement strategy making model (training the neural network model by taking the second arrangement process as training data and training the neural network model to a converged neural network model), and making a base station arrangement strategy according to first area information;
The method and the device for verifying the base station arrangement strategy are used for verifying the availability of the first arrangement process, obtaining the second arrangement process which passes the verification, performing model training on the second arrangement process, obtaining the base station arrangement strategy making model, and improving the training rationality of the base station arrangement strategy making model.
The embodiment of the invention provides a 5G base station site distribution system based on big data, which performs availability verification on a first arrangement process, and comprises the following steps:
acquiring second area information of a second area correspondingly arranged in the first arrangement process;
extracting the characteristics of the first region information to obtain a plurality of first information characteristics;
extracting the characteristics of the second region information to obtain a plurality of second information characteristics;
performing feature matching on the first information feature and the second information feature to obtain a matching value matched with the first information feature;
if the matching value is greater than or equal to a preset matching value threshold, acquiring a first information type corresponding to the first information feature or the second information feature to be matched, and associating the corresponding matching value with the first information type;
accumulating and calculating the matching value associated with the first information type to obtain a matching value sum;
If the matching value sum is greater than or equal to a preset matching value and a threshold value corresponding to the first information type, the corresponding first information type is used as a second information type;
inquiring a preset information type-criticality library, and determining the criticality of the second information type;
accumulating and calculating the criticality corresponding to each second information type, obtaining a criticality sum, and correlating with the corresponding first arrangement process;
acquiring at least one 5G base station communication abnormal event which occurs historically in the second area;
based on a preset causality analysis model, analyzing causality between the first arrangement process and the communication abnormal event to obtain a causality value;
if the cause and effect value is greater than or equal to a preset cause and effect value threshold, carrying out severity analysis on the communication abnormal event based on a preset severity analysis model, obtaining a severity value, and associating with the corresponding first arrangement process;
accumulating and calculating the criticality and the severity value associated with the first arrangement process to obtain availability;
if the availability is greater than or equal to a preset availability threshold, determining that the corresponding first arrangement process passes verification;
Otherwise, it is determined that the verification is not passed.
The working principle and the beneficial effects of the technical scheme are as follows:
the first arrangement process is not all available through big data, the area information of different areas is different and corresponds to different information characteristics (such as altitude, user density and distribution in the area, and the like), the key degree corresponding to the different information characteristics is different (such as ensuring the communication quality of the user-dense area preferentially), and if the verification is unreasonable, the selected first arrangement process is not suitable; therefore, a solution is needed;
acquiring second area information (such as topographic information, cell distribution, population density and the like of a second area corresponding to an arrangement area in a first arrangement process), performing feature extraction on the first area information (which can be realized based on a feature extraction technology), acquiring a plurality of first information features (which can be realized based on a feature extraction technology), performing feature extraction on the second area information, acquiring a plurality of second information features (which are the same as above), acquiring matching values (the larger the matching values are, the more the area information of the first area and the second area are identical), if the matching values are larger than or equal to a preset matching value threshold (such as 85), acquiring information types (such as topographic information) of the first information features to be matched, associating the matching values with the corresponding first information types, accumulating and calculating the matching values associated with the first information types, acquiring a matching value sum (the larger the matching value sum, which indicates that the similarity of the information types corresponding to the first area and the second area is higher), and if the matching value sum is larger than or equal to a preset matching value sum threshold (such as 500), taking the corresponding first information types as the second preset information types, and acquiring a key type (such as the key type, and accumulating the key type, and determining the key type, the larger the key type and the key type;
Acquiring at least one 5G base station communication abnormal event (for example, a user telephone cannot be connected) which occurs historically in a second area, based on a preset causality analysis model (the neural network model is trained by using a plurality of records for analyzing causality of the communication abnormal event as training data, the causality between a first arrangement process and the communication abnormal event is analyzed by training to a converged neural network model), acquiring a causality value (the greater the causality value is, the more the communication abnormal event is caused by the first arrangement process), if the causality value is greater than or equal to a preset causality threshold (for example, 90), based on a preset severity analysis model (the neural network model is trained by using a plurality of records for analyzing severity of the communication abnormal event manually as training data), analyzing severity of the communication abnormal event, acquiring a severity value (the greater the severity value is, the more serious the influence of the communication abnormal event is represented), accumulating and calculating the criticality and the severity value, acquiring corresponding availability, if the availability is greater than or equal to a preset availability threshold (for example, 00), judging that the first arrangement can pass through a verification process, otherwise, the first arrangement is not passed through a verification process;
The embodiment of the invention determines a matching type with high matching value based on the matching value of the first information feature and the second information feature, calculates the key sum of the first arrangement process corresponding to the second information type based on the key of the second information type matched with the matching, determines the causal value between the first arrangement process and the communication abnormal event based on the causal analysis model, determines the serious value of the first arrangement process corresponding to the communication abnormal event based on the severity analysis model, determines the availability based on the serious value and the serious value, verifies the availability of the first arrangement process, screens out the second arrangement process passing the verification, and improves the rationality of the availability verification.
The 5G base station site distribution system based on big data provided by the embodiment of the invention further comprises:
the reminding module is used for acquiring a plurality of first arrangement behaviors generated by the first staff in the first area when the first staff performs base station arrangement in the first area, judging whether the first arrangement behaviors are standard or not, and reminding the first staff if not.
The working principle and the beneficial effects of the technical scheme are as follows:
acquiring a first arrangement behavior (on-site working behavior of arrangement by a first worker, for example, adjusting an antenna angle) when the first worker performs corresponding base station arrangement in a first area, judging whether the first arrangement behavior is standard, and if not, performing corresponding processing;
According to the embodiment of the invention, based on the acquired first arrangement behaviors of the first staff, the corresponding first staff with nonstandard arrangement behaviors are processed, so that the management efficiency is improved.
The 5G base station site distribution system based on big data provided by the embodiment of the invention is characterized in that the reminding module judges whether the first arrangement behavior is standard or not, and if not, reminds the first staff, and comprises the following steps:
performing behavior specification judgment on the first arrangement behaviors based on a preset behavior specification judgment model to obtain second arrangement behaviors which are judged to be nonstandard behaviors in the first arrangement behaviors, and taking the first staff corresponding to the second arrangement behaviors as second staff;
acquiring the working position of the second staff and the first staff information;
acquiring a preset dynamic display robot distribution diagram;
based on the dynamic display robot distribution diagram, acquiring a dynamic display robot closest to the working position, and controlling the dynamic display robot to go to the working position;
when the dynamic display robot reaches the working position, controlling the dynamic display robot to acquire second personnel information of a third worker within a preset range of the working position;
Sequentially traversing the second personnel information, and taking the traversed second personnel information as third personnel information;
matching the first personnel information with the third personnel information, and taking a third staff corresponding to the matched third personnel information as a learner if the matching is met;
controlling the dynamic display robot to dynamically acquire the sight range of the learner;
analyzing the second arrangement behaviors corresponding to the learner to acquire learning items of the learner;
based on a preset display rule, controlling the dynamic display robot to dynamically display in the sight range according to the learning item;
and when the dynamic display robot finishes displaying, finishing reminding.
The working principle and the beneficial effects of the technical scheme are as follows:
when a worker performs base station arrangement, if the first arrangement behavior is irregular, the base station arrangement is unreasonable, and the quality of the whole network is further affected, so that the irregular worker needs to be reminded in time (for example, the base station arrangement is not performed according to an arrangement strategy), and a reminder needing to perform corresponding treatment is determined; therefore, a solution is needed;
Based on a preset behavior specification judging model (a neural network model is trained by using records of judging the normalization of behaviors by a plurality of workers as training data, the training is carried out to a converged neural network model), behavior specification judgment is carried out on a first arrangement behavior, an nonstandard second arrangement behavior is determined from the first arrangement behavior, meanwhile, an nonstandard second worker is determined, and the working position of the second worker (the working position can be obtained through an intelligent terminal device carried by the second worker through a GPS positioning technology) and personnel information (for example, personnel face information, construction projects and the like) are obtained;
acquiring a preset dynamic display robot distribution map (the dynamic display robot stores standard behavior data of different operation projects inside the dynamic display robot, the acquired distribution map is the dynamic position of the dynamic display robot in an operation area), acquiring the dynamic display robot closest to the working position, and controlling the dynamic display robot to go to the working position (the position of a second staff);
when the dynamic display robot reaches a working position, controlling the dynamic display robot to acquire second personnel information (such as face information of a third personnel) of the third personnel within a preset range (such as within 50 m) of the working position, determining a learner needing to be displayed from the third personnel based on a face recognition technology, controlling the dynamic display robot to acquire the sight range of the learner (the dynamic display robot acquires the visible area of the learner through a configured miniature camera), analyzing the second arrangement behavior corresponding to the learner, acquiring a learning item (such as an adjustment method of an antenna) of the learner, and controlling the dynamic display robot to dynamically display within the sight range according to the learning item based on a preset display rule (the whole process of displaying construction standard specification behavior to the first learner through a 3D holographic projection technology, and reminding that the dynamic display robot finishes displaying;
According to the embodiment of the invention, the second staff with the nonstandard first arrangement behavior is determined based on the preset behavior specification judging model, and different learning items to be learned are deeply reminded of the second staff with the nonstandard behavior through the preset dynamic display robot based on the 3D projection technology, so that the reminding effectiveness and pertinence are improved.
The 5G base station site distribution system based on big data provided by the embodiment of the invention further comprises:
the simulation module is used for performing simulation test on the 5G base station system based on the base station arrangement strategy before the base station arrangement is performed, and optimizing the base station arrangement strategy based on a test result of the simulation test;
the simulation module performs the following operations:
based on a virtual reference station technology, according to the base station arrangement strategy, setting a simulation base station in the first area to obtain a simulation 5G base station system;
based on a preset test point selection rule, acquiring a plurality of simulation test points in the simulation 5G base station system;
performing analog signal testing on the analog test point to obtain the signal strength of an analog test signal of the analog test point;
determining a test result of the simulation test according to a preset test result judging rule based on the signal strength of the simulation test signal;
And optimizing based on the test result.
The working principle and the beneficial effects of the technical scheme are as follows:
because the construction cost of the base station is high and the later position adjustment is inconvenient, the base station is simulated according to a base station arrangement strategy before construction, a simulated 5G base station system (realized by a virtual reference station technology) is obtained, a plurality of simulation test points in the simulated 5G base station system are obtained based on a preset test point selection rule (the selected position and density are selected densely in a residential area, for example), a simulation signal test is carried out on the simulation test points, the signal intensity (for example, -20 dBm) of the simulation test signals of the simulation test points is obtained, the test result of the simulation test is determined according to a preset test result determination rule (for example, if the number of test points with the signal intensity lower than-70 dBm is more than 10, the signal weakness of the simulation system is determined, and the base station arrangement needs to be adjusted);
according to the embodiment of the invention, the 5G base station system is subjected to the analog signal test before the base station is built, and the obtained analog test result provides data support for the base station arrangement effect, so that the reliability is improved.
The 5G base station site distribution system based on big data provided by the embodiment of the invention optimizes based on the simulation test result, and comprises the following steps:
Judging whether the 5G base station site distribution system needs to be optimized or not based on the test result;
if the optimization is judged to be needed, acquiring map information of the first area;
based on the map information, a two-dimensional distribution map corresponding to the map information is manufactured;
marking the signal intensity of the analog test signal on the two-dimensional distribution map;
transmitting the two-dimensional distribution diagram after marking to a preset expert node, and analyzing the interference cause of the first area by the expert node;
acquiring at least one first interference cause based on the interference cause analysis;
obtaining an interference type of the first interference cause, wherein the interference type comprises: active interference and passive interference;
when the interference type is active interference, inquiring a preset interference reason-active interference optimization scheme library to obtain at least one second interference reason;
extracting a first interference characteristic of the first interference cause, and simultaneously extracting a second interference characteristic of the second interference cause;
performing feature matching on the first interference feature and the second interference feature, and if the matching is met, acquiring a third interference feature which is met by the matching;
Inquiring a preset interference characteristic-weight value library, determining a weight value of the third interference characteristic, and correlating with the second interference cause;
accumulating and calculating the weight value associated with the second interference cause to obtain a weight value sum;
if the weight value sum is greater than or equal to a preset weight value threshold, taking the corresponding second interference reason as a third interference reason;
determining a first optimization scheme corresponding to the third interference cause based on the interference cause-active interference optimization scheme library;
acquiring a preset effect analysis model, and analyzing the first optimization scheme to obtain a first treatment effect value of the first optimization scheme;
inquiring a preset weight value and adjustment degree library, and determining the adjustment degree of a first processing effect value corresponding to the first optimization scheme based on the weight value sum of a third interference reason corresponding to the first optimization scheme;
determining a second processing effect value corresponding to the first optimization scheme based on the first processing effect value corresponding to the first optimization scheme and the adjustment degree;
determining a first optimization scheme with the maximum second treatment effect value as a second optimization scheme;
scheduling the first staff member for optimization based on the second optimization scheme;
When the interference type is passive interference, a preset judgment ring is obtained, and the judgment ring is controlled to randomly displace in the two-dimensional distribution diagram;
based on the signal intensity of the analog test signal, judging a third area needing to be optimized in the two-dimensional distribution diagram according to a preset judgment circle judgment rule;
acquiring a complaint log of the user in the third area;
analyzing the complaint log to obtain a complaint piece area of a complaint user corresponding to the two-dimensional distribution map;
notifying a detector closest to the complaint zone to carry detection equipment to the complaint zone;
when the detection personnel reach the complaint piece area, detecting interference equipment in a fourth area of the preset range of the complaint piece area;
detecting the interference equipment in the fourth area based on a preset interference detection rule, and determining the interference equipment in the fourth area;
acquiring an equipment management side of the interference equipment, and coordinating with the equipment management side based on a preset coordination rule;
if the coordination is successful, the optimization is completed;
if coordination fails, a preset base station adjustment strategy library is obtained, and a base station adjustment strategy for the interference equipment is determined based on a third interference reason of the interference equipment;
Based on the base station adjustment strategy, adjusting the base station arrangement strategy to obtain an adjusted optimal arrangement strategy;
and scheduling the first staff to conduct 5G base station site distribution in the first area based on the optimal arrangement strategy.
The working principle and the beneficial effects of the technical scheme are as follows:
when the system test is carried out on the simulated 5G base station system, different signal interference reasons are determined according to the test result, and different optimization modes of the interference reasons are also different; therefore, a solution is needed;
judging whether optimization is needed or not based on a test result, if so, acquiring map information (such as distribution of buildings and roads) in a preset range of a first area, acquiring a two-dimensional distribution diagram corresponding to the map information based on the map information, marking a simulation test result on the two-dimensional distribution diagram, sending the two-dimensional distribution diagram to a preset expert node (such as XX wireless communication company technical department), analyzing interference reasons of the first area by the expert node, acquiring at least one first interference reason (such as unreasonable base station parameter setting), and acquiring interference types of the first interference reason, wherein the interference types comprise: active interference (e.g., unreasonable base station parameter settings) and passive interference (e.g., a communication coverage area user privately installs a mobile signal amplifier);
When the interference type is active interference, inquiring a local interference cause-active interference optimization scheme library (a database for storing active interference and corresponding schemes processed by the engineering team historically), acquiring at least one second interference cause, extracting a first interference feature of the first interference cause (based on feature extraction technology, such as voice distortion in a conversation process), simultaneously extracting a second interference feature of the second interference cause (the same principle), performing feature matching on the first interference feature and the second interference feature, acquiring the matching with a third interference feature if the matching is matched, inquiring a preset interference feature-weight value library (the database for storing the interference feature and the weight value thereof), determining the weight value of the third interference feature, wherein the larger the weight value is, the larger the influence of the third interference feature is represented, accumulating the weight value associated with the second interference cause, obtaining a weight value sum, and taking the corresponding second interference cause as the third interference cause (the interference feature with high similarity), performing artificial training of the first interference feature-based on the matching with the third interference feature, performing training model, performing the training of the training model by adopting the first interference feature-matching optimization scheme (the preset interference feature and the first interference feature is stored), performing the training model, performing the training of the training model is optimized, obtaining a first processing effect value of the first optimization scheme (the first optimization scheme corresponds to an effect of the third interference cause corresponds to the interference), querying a preset weight value and an adjustment degree library (a database storing weight values and adjustment values for adjustment degrees of the first processing effect value), and determining an adjustment degree of the first optimization scheme based on the weight value and the adjustment value of the first optimization scheme corresponding to the third interference cause (for example: 0.9), determining a second processing effect value corresponding to the first optimization scheme (the higher the second processing effect value is, the more suitable the corresponding first optimization scheme is), determining the first optimization scheme with the largest second processing effect value as the second optimization scheme (screening out the most suitable optimization scheme), performing corresponding optimization by a first staff (for example, readjusting parameters of a base station, adjusting pitch angle of an antenna, and the like), acquiring a preset judgment ring (a closed area of a preset range) when the interference type is passive interference, controlling the judgment ring to randomly displace in a two-dimensional distribution diagram, analyzing the complaint log (a complaint log record of a user, for example, in the case of XX, of a certain cell) in the two-dimensional distribution diagram according to a simulation test result, according to a preset judgment ring judgment rule (a preset rule for determining the area to be optimized, for example, when 10 or more-120 dBm data are generated in simulation test result data, determining the corresponding area of the two-dimensional distribution diagram area where the current judgment ring is located is mapped in the first area to be the area to be optimized), judging a third area to be optimized in the two-dimensional distribution diagram, acquiring a complaint log records of users in the third area to be complaint log of users in the two-dimensional distribution diagram (for example, in the case of XX, in the certain cell, acquiring a complaint zone (such as an XX cell) corresponding to a two-dimensional distribution map, informing a detector closest to the complaint zone of carrying detection equipment (such as a handheld NR sweep generator) to the complaint zone, performing interference equipment detection in a fourth area of a preset range of the complaint zone when the detector arrives at the complaint zone, performing interference equipment detection in the fourth area according to a preset interference detection mode (such as determining an interference source according to a gradient of a signal weakening or a gradient of an interfered intensity), determining interference equipment in the fourth area (such as a video monitoring equipment in an elevator), acquiring an equipment management side (such as an XX company) of the interference equipment, performing coordination based on a preset coordination mode (such as coordinating a frequency band of a remote transmission signal by a partner company), and performing the coordination by the equipment management side, if the coordination is successful, performing the optimization, and determining an alternative interference equipment (such as adding a small-area base station adjustment strategy) for the interference equipment based on a preset base station adjustment strategy library (storing other base station adjustment strategy obtained from big data) if the coordination is failed;
The embodiment of the invention determines the interference reason of the simulated 5G base station system based on the simulation test result obtained by the monitoring trolley and expert analysis, determines a proper optimization scheme based on the reason type, and improves the optimization efficiency.
The invention provides a 5G base station address distribution method based on big data, which further comprises the following steps of
The user verification module is used for carrying out user verification on the user when the user inputs a request for uploading the complaint log, and if the user passes the verification, the user is allowed to upload the complaint log;
wherein performing user authentication on the user comprises:
acquiring the user uploading identity verification information;
splitting the identity verification information to obtain a plurality of information items;
obtaining an information type corresponding to the information item, wherein the information type comprises: primary information and secondary information;
when the information type is main information, acquiring a first integrity and a main value corresponding to the information item based on a preset integrity analysis model;
when the information type is auxiliary information, acquiring a second integrity and an auxiliary value corresponding to the information item based on the integrity analysis model;
calculating a verification value of the user based on the first integrity, the primary value, the second integrity and the secondary value;
When the verification value is greater than or equal to a preset verification value threshold, the user is authenticated;
otherwise, not pass.
The working principle and the beneficial effects of the technical scheme are as follows:
the acquired identity verification information uploaded by the user comprises (identity information, complaint content and the like of the user), the identity verification information is subjected to information splitting to obtain a plurality of information items (such as name items, number items, address items and the like), and the acquired information types corresponding to the information items comprise: main information (key information) and auxiliary information (other information for auxiliary verification), when the information type is the main information, based on a preset integrity analysis model (a neural network model is trained by using records of integrity analysis of the information by a plurality of people as training data, the neural network model is trained to be converged), a first integrity and a main value of a corresponding information item (the key degree of the information item is higher, the key is higher) are obtained, when the information type is the auxiliary information, a second integrity and an auxiliary value (the degree of auxiliary verification) of the corresponding information item are obtained based on the integrity analysis model (the principle is the same), and based on the first integrity, the main value, the second integrity and the auxiliary value, a verification value of a user is calculated, and a calculation formula is as follows:
Wherein ρ is the verification value, w i For the ith said first complete value, k i For the ith said principal value, n 1 The total number, w, of information items of which the information type is the main information j For the j-th said second complete value, l j Is the j thThe auxiliary value, n 2 Is the total number of information items of which the information type is auxiliary information, gamma 1 And gamma 2 The weight is preset;
when the verification value is greater than or equal to a preset verification value threshold (for example, 100), the user passes identity verification;
the embodiment of the invention carries out splitting of information items on the authentication information based on the acquired authentication information of the user, determines the authentication value based on the integrity degree, the main degree and the auxiliary authentication degree which can help authentication of the information provided by the user, authenticates the user applying for complaints, reduces the probability of malicious uploading, and is more beneficial to solving the complaints in a targeted way through real-name authentication.
The invention provides a 5G base station site distribution method based on big data, as shown in figure 2, comprising the following steps:
step S1: acquiring first area information of a first area needing to be subjected to 5G base station address distribution;
step S2: based on big data technology, formulating a base station arrangement strategy of the first area according to the first area information;
Step S3: and dispatching a plurality of first staff to perform base station arrangement in the first area according to the base station arrangement strategy, and completing 5G base station site arrangement after the base station arrangement is completed.
The working principle and the beneficial effects of the technical scheme are described in the method claims and are not repeated.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. A big data based 5G base station site placement system, comprising:
the acquisition module is used for acquiring first area information of a first area needing to be subjected to 5G base station address distribution;
the formulating module is used for formulating a base station arrangement strategy of the first area according to the first area information based on big data technology;
the execution module is used for scheduling a plurality of first staff to perform base station arrangement in the first area according to the base station arrangement strategy, and completing the 5G base station site arrangement after the base station arrangement is completed;
Wherein, the formulation module performs the following operations:
based on a big data technology, acquiring a plurality of first arrangement processes for manually performing 5G base station site arrangement;
verifying the availability of the first arrangement process, and taking the verified first arrangement process as a second arrangement process;
based on a preset model training algorithm, performing model training according to all the second arrangement processes to obtain a base station arrangement strategy making model;
formulating a base station arrangement strategy of the first area according to the first area information based on the base station arrangement strategy formulation model;
wherein said verifying availability of said first placement procedure comprises:
acquiring second area information of a second area correspondingly arranged in the first arrangement process;
extracting the characteristics of the first region information to obtain a plurality of first information characteristics;
extracting the characteristics of the second region information to obtain a plurality of second information characteristics;
performing feature matching on the first information feature and the second information feature to obtain a matching value matched with the first information feature;
if the matching value is greater than or equal to a preset matching value threshold, acquiring a first information type corresponding to the first information feature or the second information feature to be matched, and associating the corresponding matching value with the first information type;
Accumulating and calculating the matching value associated with the first information type to obtain a matching value sum;
if the matching value sum is greater than or equal to a preset matching value and a threshold value corresponding to the first information type, the corresponding first information type is used as a second information type;
inquiring a preset information type-criticality library, and determining the criticality of the second information type;
accumulating and calculating the criticality corresponding to each second information type, obtaining a criticality sum, and correlating with the corresponding first arrangement process;
acquiring at least one 5G base station communication abnormal event which occurs historically in the second area;
based on a preset causality analysis model, analyzing causality between the first arrangement process and the communication abnormal event to obtain a causality value;
if the cause and effect value is greater than or equal to a preset cause and effect value threshold, carrying out severity analysis on the communication abnormal event based on a preset severity analysis model, obtaining a severity value, and associating with the corresponding first arrangement process;
accumulating and calculating the criticality and the severity value associated with the first arrangement process to obtain availability;
If the availability is greater than or equal to a preset availability threshold, determining that the corresponding first arrangement process passes verification;
otherwise, it is determined that the verification is not passed.
2. The big data based 5G base station addressing system of claim 1, further comprising:
the reminding module is used for acquiring a plurality of first arrangement behaviors generated by the first staff in the first area when the first staff performs base station arrangement in the first area, judging whether the first arrangement behaviors are standard or not, and reminding the first staff if not.
3. The big data based 5G base station location system of claim 2, wherein the reminding module determines whether the first arrangement behavior is normal, and if not, reminds the first staff member, comprising:
performing behavior specification judgment on the first arrangement behaviors based on a preset behavior specification judgment model to obtain second arrangement behaviors which are judged to be nonstandard behaviors in the first arrangement behaviors, and taking the first staff corresponding to the second arrangement behaviors as second staff;
acquiring the working position of the second staff and the first staff information;
Acquiring a preset dynamic display robot distribution diagram;
based on the dynamic display robot distribution diagram, acquiring a dynamic display robot closest to the working position, and controlling the dynamic display robot to go to the working position;
when the dynamic display robot reaches the working position, controlling the dynamic display robot to acquire second personnel information of a third worker within a preset range of the working position;
sequentially traversing the second personnel information, and taking the traversed second personnel information as third personnel information;
matching the first personnel information with the third personnel information, and taking a third staff corresponding to the matched third personnel information as a learner if the matching is met;
controlling the dynamic display robot to dynamically acquire the sight range of the learner;
analyzing the second arrangement behaviors corresponding to the learner to acquire learning items of the learner;
based on a preset display rule, controlling the dynamic display robot to dynamically display in the sight range according to the learning item;
and when the dynamic display robot finishes displaying, finishing reminding.
4. The big data based 5G base station addressing system of claim 1, further comprising:
the simulation module is used for performing simulation test on the 5G base station system based on the base station arrangement strategy before the base station arrangement is performed, and optimizing the base station arrangement strategy based on a test result of the simulation test;
the simulation module performs the following operations:
based on a virtual reference station technology, according to the base station arrangement strategy, setting a simulation base station in the first area to obtain a simulation 5G base station system;
based on a preset test point selection rule, acquiring a plurality of simulation test points in the simulation 5G base station system;
performing analog signal testing on the analog test point to obtain the signal strength of an analog test signal of the analog test point;
determining a test result of the simulation test according to a preset test result judging rule based on the signal strength of the simulation test signal;
and optimizing based on the test result.
5. The big data based 5G base station addressing system of claim 4, wherein said optimizing based on said simulation test results comprises:
Judging whether the 5G base station site distribution system needs to be optimized or not based on the test result;
if the optimization is judged to be needed, acquiring map information of the first area;
based on the map information, a two-dimensional distribution map corresponding to the map information is manufactured;
marking the signal intensity of the analog test signal on the two-dimensional distribution map;
transmitting the two-dimensional distribution diagram after marking to a preset expert node, and analyzing the interference cause of the first area by the expert node;
acquiring at least one first interference cause based on the interference cause analysis;
obtaining an interference type of the first interference cause, wherein the interference type comprises: active interference and passive interference;
when the interference type is active interference, inquiring a preset interference reason-active interference optimization scheme library to obtain at least one second interference reason;
extracting a first interference characteristic of the first interference cause, and simultaneously extracting a second interference characteristic of the second interference cause;
performing feature matching on the first interference feature and the second interference feature, and if the matching is met, acquiring a third interference feature which is met by the matching;
Inquiring a preset interference characteristic-weight value library, determining a weight value of the third interference characteristic, and correlating with the second interference cause;
accumulating and calculating the weight value associated with the second interference cause to obtain a weight value sum;
if the weight value sum is greater than or equal to a preset weight value threshold, taking the corresponding second interference reason as a third interference reason;
determining a first optimization scheme corresponding to the third interference cause based on the interference cause-active interference optimization scheme library;
acquiring a preset effect analysis model, and analyzing the first optimization scheme to obtain a first treatment effect value of the first optimization scheme;
inquiring a preset weight value and adjustment degree library, and determining the adjustment degree of a first processing effect value corresponding to the first optimization scheme based on the weight value sum of a third interference reason corresponding to the first optimization scheme;
determining a second processing effect value corresponding to the first optimization scheme based on the first processing effect value corresponding to the first optimization scheme and the adjustment degree;
determining a first optimization scheme with the maximum second treatment effect value as a second optimization scheme;
scheduling the first staff member for optimization based on the second optimization scheme;
When the interference type is passive interference, a preset judgment ring is obtained, and the judgment ring is controlled to randomly displace in the two-dimensional distribution diagram;
based on the signal intensity of the analog test signal, judging a third area needing to be optimized in the two-dimensional distribution diagram according to a preset judgment circle judgment rule;
acquiring a complaint log of the user in the third area;
analyzing the complaint log to obtain a complaint piece area of a complaint user corresponding to the two-dimensional distribution map;
notifying a detector closest to the complaint zone to carry detection equipment to the complaint zone;
when the detection personnel reach the complaint piece area, detecting interference equipment in a fourth area of the preset range of the complaint piece area;
detecting the interference equipment in the fourth area based on a preset interference detection rule, and determining the interference equipment in the fourth area;
acquiring an equipment management side of the interference equipment, and coordinating with the equipment management side based on a preset coordination rule;
if the coordination is successful, the optimization is completed;
if coordination fails, a preset base station adjustment strategy library is obtained, and a base station adjustment strategy for the interference equipment is determined based on a third interference reason of the interference equipment;
Based on the base station adjustment strategy, adjusting the base station arrangement strategy to obtain an adjusted optimal arrangement strategy;
and scheduling the first staff to conduct 5G base station site distribution in the first area based on the optimal arrangement strategy.
6. The 5G base station site distribution method based on big data is characterized by comprising the following steps:
step S1: acquiring first area information of a first area needing to be subjected to 5G base station address distribution;
step S2: based on big data technology, formulating a base station arrangement strategy of the area according to the first area information;
step S3: scheduling a plurality of first staff to perform base station arrangement in the first area according to the base station arrangement strategy, and completing 5G base station site arrangement after the base station arrangement is completed;
wherein, the step S2: based on big data technology, according to the first area information, formulating a base station arrangement strategy of the area, including:
based on a big data technology, acquiring a plurality of first arrangement processes for manually performing 5G base station site arrangement;
verifying the availability of the first arrangement process, and taking the verified first arrangement process as a second arrangement process;
Based on a preset model training algorithm, performing model training according to the second arrangement process to obtain a base station arrangement strategy making model;
formulating a base station arrangement strategy according to the first area information based on the base station arrangement strategy formulation model;
wherein said verifying availability of said first placement procedure comprises:
acquiring second area information of a second area correspondingly arranged in the first arrangement process;
extracting the characteristics of the first region information to obtain a plurality of first information characteristics;
extracting the characteristics of the second region information to obtain a plurality of second information characteristics;
performing feature matching on the first information feature and the second information feature to obtain a matching value matched with the first information feature;
if the matching value is greater than or equal to a preset matching value threshold, acquiring a first information type corresponding to the first information feature or the second information feature to be matched, and associating the corresponding matching value with the first information type;
accumulating and calculating the matching value associated with the first information type to obtain a matching value sum;
if the matching value sum is greater than or equal to a preset matching value and a threshold value corresponding to the first information type, the corresponding first information type is used as a second information type;
Inquiring a preset information type-criticality library, and determining the criticality of the second information type;
accumulating and calculating the criticality corresponding to each second information type, obtaining a criticality sum, and correlating with the corresponding first arrangement process;
acquiring at least one 5G base station communication abnormal event which occurs historically in the second area;
based on a preset causality analysis model, analyzing causality between the first arrangement process and the communication abnormal event to obtain a causality value;
if the cause and effect value is greater than or equal to a preset cause and effect value threshold, carrying out severity analysis on the communication abnormal event based on a preset severity analysis model, obtaining a severity value, and associating with the corresponding first arrangement process;
accumulating and calculating the criticality and the severity value associated with the first arrangement process to obtain availability;
if the availability is greater than or equal to a preset availability threshold, determining that the corresponding first arrangement process passes verification;
otherwise, it is determined that the verification is not passed.
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