CN107276785A - A kind of WLAN optimization method and device - Google Patents
A kind of WLAN optimization method and device Download PDFInfo
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- CN107276785A CN107276785A CN201710303778.3A CN201710303778A CN107276785A CN 107276785 A CN107276785 A CN 107276785A CN 201710303778 A CN201710303778 A CN 201710303778A CN 107276785 A CN107276785 A CN 107276785A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/04—Processing captured monitoring data, e.g. for logfile generation
- H04L43/045—Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
- H04W84/10—Small scale networks; Flat hierarchical networks
- H04W84/12—WLAN [Wireless Local Area Networks]
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Abstract
The invention discloses a kind of WLAN WLAN optimization methods, this method includes：Receive the data of wlan network equipment collection；Analysis model is set up by the intelligent algorithm of machine learning, the data analyzed using analysis model；Network Optimization Strategy is determined according to the result of the analysis and execution is issued.By the wireless environment data, the user experience data that receive the whole net that wlan network equipment is gathered, it is pooled to cloud platform and carries out analysis calculating, the technical advantage of machine learning is made full use of to analyze data, obtain whole net wireless environment and network operation trend, Consumer's Experience situation, it is determined that optimal Network Optimization Strategy, the feedback of network optimization effect can also be obtained by analysis model, with further reference to Consumer's Experience situation, Network Optimization Strategy adjustment is carried out, is realized using Consumer's Experience as the optimal network optimization.
Description
Technical field
The present invention relates to communication technical field, espespecially a kind of WLAN (Wireless Local Area
Network, WLAN) optimization method and device.
Background technology
In recent years, the WLAN based on IEEE802.11 agreements is with the technology fast development of its advantage and maturation that protrude, quilt
It is widely used in the network structions such as market, enterprise, hospital, school and meeting-place.
In the enterprise-level wlan network of sizable application, limited not overlapping communication channel is limited to so that network interferences,
The network optimization problems such as load balancing, terminal access become increasingly complex.Because wireless access points (AP) equipment scale is huge
Greatly, in terms of channel plan, manually planning needs to expend substantial amounts of human cost merely, and utilizes AC automatic channel to adjust
It is whole, there is the problem of convergence time is long again.
Current wlan network optimizes, it is necessary to balance interference and cover in terms of power programming, and because each AP has difference
Region physical environment, it is impossible to completely replicate；In terms of roaming and access, the roaming associated radio frequency parameter of large amount of complex needs control
System adjustment；In terms of effect examination, it is also desirable to which a large amount of manpowers carry out point bit test and checked and accepted.It is existing main automatic by radio frequency resource
Optimum management, the problem of solving radio communication channel spectral interference, is scanned to the network of surrounding by WAP, obtained
Take radio frequency environment information and carry out network interferences assessment, it is then automatic to carry out the network planning, lift network performance.However, channel
Automation adjustment needs to gather a large amount of environmental informations, according to collection data separation present networks and the interference information of non-present networks, meter
Calculating WLAN actual interferences degree and channel saturation degree, here, the centralized calculation mode according to access controller (AC) will cause
The storage of controller and Calculation bottleneck；According to AP distributed computing, then it can cause the optimization long drawn game of convergence time
Portion most preferably substitutes the optimal error of whole net；And frequently dynamic adjustment also can cause terminal device frequently to switch access channel
And cause practical application experience not good.
The content of the invention
The embodiment of the present invention provides a kind of WLAN optimization methods and device, to solve wlan network optimization in the prior art
The problem of effect is poor, user's real experiences are bad.
A kind of WLAN WLAN optimization methods, methods described includes：
Receive the data of wlan network equipment collection；
Analysis model is set up by the intelligent algorithm of machine learning, the data analyzed using analysis model；
Network Optimization Strategy is determined according to the result of the analysis and execution is issued.
Optionally, the data for receiving the collection of wlan network equipment, including：
The network equipment running state data, wireless environment data, user experience data of wlan network equipment collection are received,
Wherein, the data are wireless controller AC, wireless access point AP progress data acquisition and carry out squeeze operation transmission.
Optionally, it is described that analysis model is set up by the intelligent algorithm of machine learning, using analysis model to the data
Analyzed, including：
By the intelligent algorithm of machine learning, set up wireless environment and perceive trend model, Consumer's Experience sensor model；
Based on the data, perceive trend model analysis using wireless environment and obtain whole net WLAN wireless environments covering feelings
Condition, disturbed condition and network operation state trend, reduce wireless communication status, are used using Consumer's Experience sensor model assay measures
Family experience situation, and all Consumer's Experience situations of the wireless communication status and whole net are visualized.
Optionally, it is described to determine Network Optimization Strategy and issue execution, including：
The Consumer's Experience situation obtained according to wireless WLAN environment and equipment running status and analysis, to described wireless
Network state is diagnosed, and analyzes the radio network problems existed, Network Optimization Strategy is determined for the radio network problems
And execution is issued, wherein, the radio network problems include interference, access, the one or more of roaming.
Optionally, methods described, in addition to：
Network Optimization Strategy is issued after execution, and obtaining wireless communication status by analysis model analysis feeds back, and joins
Consumer's Experience situation and wireless communication status difference before and after being performed according to Network Optimization Strategy, carry out the tune of Network Optimization Strategy
It is whole, realize that closed loop restrains.
A kind of WLAN optimizes device, including：Receiving unit, analytic unit, policy unit；Wherein,
Receiving unit, the data for receiving the collection of wlan network equipment；
Analytic unit, for setting up analysis model by the intelligent algorithm of machine learning, using analysis model to the number
According to being analyzed；
Policy unit, for determining Network Optimization Strategy according to the result of the analysis and issuing execution.
Optionally, the receiving unit, the network equipment running status number specifically for receiving the collection of wlan network equipment
According to, wireless environment data, user experience data, wherein, the data be wireless controller AC, wireless access point AP carry out data
Gather and carry out squeeze operation transmission.
Optionally, the analytic unit, specifically for the intelligent algorithm by machine learning, sets up wireless environment and perceives
Potential model, Consumer's Experience sensor model；Based on the data, perceive trend model analysis using wireless environment and obtain whole net WLAN
Wireless environment coverage condition, disturbed condition and network operation state trend, are reduced wireless communication status, are perceived using Consumer's Experience
Model analysis measure user experience situation, and can by all Consumer's Experience situations progress of the wireless communication status and whole net
Depending on change.
Optionally, the policy unit, specifically for being obtained according to wireless WLAN environment and equipment running status and analysis
The Consumer's Experience situation, the wireless communication status is diagnosed, analyze exist radio network problems, for described
Radio network problems determine Network Optimization Strategy and issue execution, wherein, the radio network problems include interference, access, unrestrained
The one or more of trip.
Optionally, the analytic unit, is additionally operable to after Network Optimization Strategy issues execution, passes through the analysis model point
Analysis obtains wireless communication status feedback, and with reference to the Consumer's Experience situation and wireless communication status before and after Network Optimization Strategy execution
Difference, carries out the adjustment of Network Optimization Strategy, realizes that closed loop restrains.
The present invention has the beneficial effect that：
WLAN optimization method and devices provided in an embodiment of the present invention, by receiving the whole net that wlan network equipment is gathered
Network equipment running state data, wireless environment data, user experience data, are pooled to cloud platform and carry out analysis calculating, fully
Data are analyzed using the technical advantage of machine learning, whole net wireless environment and network operation trend, Consumer's Experience is obtained
Situation, it is determined that optimal Network Optimization Strategy, can also obtain the feedback of network optimization effect by analysis model, further joins
According to Consumer's Experience situation, Network Optimization Strategy adjustment is carried out, is realized using Consumer's Experience as the optimal network optimization.
Brief description of the drawings
Fig. 1 is the flow chart of WALN optimization methods in the embodiment of the present invention；
Fig. 2 is the structural representation of WLAN optimization devices in the embodiment of the present invention；
Fig. 3 is the system architecture diagram in the embodiment of the present invention using WLAN optimization methods.
Embodiment
It is poor for wlan network effect of optimization present in prior art, the problem of user's real experiences are bad, the present invention
The WLAN optimization methods that embodiment is provided, first, the flow of the inventive method is as shown in figure 1, execution step is as follows：
Step 101, the data of wlan network equipment collection are received；
Here, the data received are that AC, AP carry out data acquisition control, and the data to collection are compressed operation, profit
Sent with https encryption technologies by specific passage to the data platform in high in the clouds.The data mainly include the network equipment and run
Status data, wireless environment data, user experience data etc., wherein, specifically include AP, AC equipment operational factor and each AP weeks
Environmental information of eating dishes without rice or wine, the access behavioral parameters of user terminal, WLAN WIFI performance parameters, Consumer's Experience measurement parameter for enclosing etc.
Deng.
Step 102, analysis model is set up by the intelligent algorithm of machine learning, the data carried out using analysis model
Analysis；
Specifically, by the intelligent algorithm of machine learning, set up wireless environment and perceive trend model, Consumer's Experience perception mould
Type；Based on the data, perceive trend model analysis using wireless environment and obtain whole net WLAN wireless environments coverage condition, interference
Situation and network operation state trend, reduce wireless communication status, utilize Consumer's Experience sensor model assay measures Consumer's Experience
Situation, and all Consumer's Experience situations of the wireless communication status and whole net are subjected to visual data models encapsulation with can
Depending on change display, the visual user experience can be used for problem identification, the analysis of causes and Network Optimization Strategy selection and after
Continuous effect of optimization is examined.
Step 103, Network Optimization Strategy is determined according to the result of the analysis and issues execution.
Specifically, the Consumer's Experience situation obtained according to wireless WLAN environment and equipment running status and analysis, to described
Wireless communication status is diagnosed, and according to making Consumer's Experience reach optimal optimization principles, analyzes the radio network problems existed,
For radio network problems such as interference, access, roamings, determine Network Optimization Strategy and issue execution.
Here, for radio network problems such as interference, access, roamings, there is provided the network based on intelligent analysis algorithm is excellent
Change strategy, such as intelligent RF resource management (RRM), intelligence access, intelligent roaming network optimization solution.Network optimization plan
Slightly perform and specifically include：
Coverage evaluating, traditional coverage evaluating typically uses two ways：Temperature-sensitive figure and artificial Point Measurement.Temperature-sensitive figure is to letter
Number emulated, it is impossible to predict the true motion track of the network user, and consumption is needed by the way of the scanning of artificial single point signals
Take the substantial amounts of time.Therefore, the network design designed in the embodiment of the present invention is that where wireless signal is accomplished by based on user
Basic thought where, the assessment covered with reference to user terminal wireless index so that the signal of overlay area is strong covered
Degree meets the demand of user, and feeds back with this coverage condition of most live network demand.
Interference optimization, analyzes the neighborhood between AP, and interference is visualized based on whole network data.Comprehensive analysis
And be automatically adjusted, co-channel interference and adjacent frequency interference between reduction Home Network AP, between Home Network AP and non-Home Network wireless device.
Access roaming optimizes, and terminal typically selects the first element using signal intensity as access, but can not before optimization
Reach optimum experience.Predicted accordingly, it would be desirable to be accessed to experience after situation and access according to terminal, allow terminal either accessing also
It is that can reach optimum experience in the roaming stage.
Machine learning, using machine learning engine, constantly learns Consumer's Experience, network characteristic, optimisation strategy so that network
Possesses the ability of self-optimization, all the time in splendid Consumer's Experience state.
Further, this method can also include：Network Optimization Strategy is issued after execution, is analyzed by above-mentioned analysis model
Wireless communication status feedback is obtained, and with reference to Consumer's Experience situation, carries out the adjustment of Network Optimization Strategy, realizes that closed loop restrains.
The WLAN optimization methods that the present invention is provided, by receiving the network equipment running status number that wlan network equipment is gathered
According to, the wireless environment data of whole net, user experience data, be pooled to cloud platform carry out analysis calculating, make full use of machine learning
Technical advantage data are analyzed, whole net wireless environment and network operation trend, Consumer's Experience situation are obtained, it is determined that most preferably
Network Optimization Strategy, the feedback of network optimization effect can also be obtained by analysis model, with further reference to Consumer's Experience feelings
Condition, carries out Network Optimization Strategy adjustment, realizes using Consumer's Experience as the optimal network optimization.
Based on same inventive concept, the embodiment of the present invention a kind of WLAN optimizations device, structure are provided as shown in Fig. 2 including：
Receiving unit 21, analytic unit 22, policy unit 23；Wherein,
Receiving unit 21, the data for receiving the collection of wlan network equipment；Here, the data received are that AC, AP enter
Row data acquisition control, the data to collection are compressed operation, using https encryption technologies by specific passage send to
The data platform in high in the clouds.The data mainly include network equipment running state data, wireless environment data, user experience data
Deng, wherein, specifically include environmental information of eating dishes without rice or wine around AP, AC equipment operational factor and each AP, the access row of user terminal
For parameter, WLAN WIFI performance parameters, Consumer's Experience measurement parameter etc..
Analytic unit 22, for setting up analysis model by the intelligent algorithm of machine learning, using analysis model to described
Data are analyzed；By the intelligent algorithm of machine learning, set up wireless environment and perceive trend model, Consumer's Experience perception mould
Type；Based on the data, perceive trend model analysis using wireless environment and obtain whole net WLAN wireless environments coverage condition, interference
Situation and network operation state trend, reduce wireless communication status, utilize Consumer's Experience sensor model assay measures Consumer's Experience
Situation, and all Consumer's Experience situations of the wireless communication status and whole net are subjected to visual data models encapsulation with can
Depending on change display, the visual user experience can be used for problem identification, the analysis of causes and Network Optimization Strategy selection and after
Continuous effect of optimization is examined.
Policy unit 23, for determining Network Optimization Strategy according to the result of the analysis and issuing execution.Specifically, root
The Consumer's Experience situation obtained according to wireless WLAN environment and equipment running status and analysis, is examined the wireless communication status
It is disconnected, according to making Consumer's Experience reach optimal optimization principles, the radio network problems existed are analyzed, for interference, access, roaming
Deng radio network problems, determine Network Optimization Strategy and issue execution.
Wherein, the receiving unit 21, the network equipment running status number specifically for receiving the collection of wlan network equipment
According to, wireless environment data, user experience data, wherein, the data be AC, AP carry out data acquisition and be compressed desensitization behaviour
Make what is sent.
Wherein, the analytic unit 22, specifically for the intelligent algorithm by machine learning, sets up wireless environment and perceives
Potential model, Consumer's Experience sensor model；Based on the data, perceive trend model analysis using wireless environment and obtain whole net WLAN
Wireless environment coverage condition, disturbed condition and network operation state trend, are reduced wireless communication status, are perceived using Consumer's Experience
Model analysis measure user experience situation, and wireless communication status and whole net institute Consumer's Experience situation are visualized.
Wherein, the policy unit 23, specifically for the Consumer's Experience situation and wireless WLAN environment obtained according to analysis
And equipment running status, the wireless communication status is diagnosed, the radio network problems existed is analyzed, determines the network optimization
Strategy simultaneously issues execution, wherein, the radio network problems include interference, access, the one or more of roaming.
Optionally, the analytic unit 22, is additionally operable to after Network Optimization Strategy issues execution, passes through the analysis model
Analysis obtains wireless communication status feedback, and with reference to the Consumer's Experience situation and wireless network shape before and after Network Optimization Strategy execution
State difference, carries out the adjustment of Network Optimization Strategy, realizes that closed loop restrains.
It should be appreciated that shown in WLAN optimization device realization principles provided in an embodiment of the present invention and process and above-mentioned Fig. 1
Embodiment is similar, will not be repeated here.
WLAN provided in an embodiment of the present invention optimizes device, by the wireless ring for receiving the whole net that wlan network equipment is gathered
Border data, user experience data, are pooled to cloud platform and carry out analysis calculating, make full use of the technical advantage of machine learning to data
Analyzed, obtain whole net wireless environment and network operation trend, Consumer's Experience situation, it is determined that optimal Network Optimization Strategy,
The feedback of network optimization effect can also be obtained by analysis model, with further reference to Consumer's Experience situation, the network optimization is carried out
Developing Tactics, are realized using Consumer's Experience as the optimal network optimization.
The embodiment of the present invention also provides a kind of system assumption diagram of application WLAN optimization methods, as shown in figure 3, the system
Layer of structure is divided into：Presentation layer, big data analysis layer, equipment acquisition layer；Wherein, big data analysis layer is further divided into：
MAC layer, data storage layer, machine learning layer, intelligent network optimization solution layer.
Specifically, equipment acquisition layer, mainly carries out data acquisition control by AC, AP, https encryption technologies and big number are utilized
Authentication and data interaction, and operation that the data of collection are compressed and desensitized are carried out according to analysis layer.What this layer was collected
Data mainly include：The access behavior ginseng of environmental information of eating dishes without rice or wine, user terminal around AP, AC equipment operational factor and each AP
Number, WLAN WIFI performance parameters, Consumer's Experience measurement parameter etc..
Big data analysis layer, major function is that wlan network device periodically is gathered to the data uploaded to be stored, divided
Analysis, study.The business processing data volume of this layer and wlan network equipment scale and network user's scale are proportional.It is divided into following several
Individual sublayer：
(1) MAC layer, this layer realizes the data acquisition interface and access control between wlan network equipment.Pass through
Https cryptographic protocols and data compression scheme, authentication information is interacted with wlan network equipment, is received by wlan network equipment
The wireless network environment data that upload of device port and user experience data etc., and intelligent network optimization solution layer is generated
Optimal Parameters issued.The layer supports distributed capture, by way of clustered control, load balancing, realizes many data
Concurrent and high frequency acquisition the function in source.
(2) data storage layer, this layer realizes the storage to gathered data, and machine learning layer is provided based on initial data
Storage, realize hierarchical data storage, safe and reliable basic data provided for upper-layer service.Data storage layer can be with
Needed to provide business model data according to business, and directly visualized.
(3) machine learning layer, major function includes：First, the wireless environment parameter uploaded using wlan network equipment, point
The whole net wireless environment of analysis prediction and network operation state trend；Secondly, the user experience data assay measures user of collection is utilized
Experience situation；Finally, continuous learning terminal Consumer's Experience and intelligent network optimization solution, the strategy of adjust automatically network optimization scheme,
Make up to optimum efficiency.
(4) intelligent network optimization solution layer, realizes and is directed to radio network optimization problem, using machine learning result and
Distributed computing fabric realizes intelligent RF resource management (RRM), intelligence there is provided corresponding intelligent solution and algorithm
Access (based on terminal access behavioural analysis optimal access optimization), intelligent roaming (based on terminal history roaming specificity analysis and
The roaming guiding optimization of environmental strategies) etc..
Presentation layer, can provide the interactive interface with user, and complicated wireless network visual pattern is shown simultaneously
And combine service application effect.On the one hand, underlying traffic data are presented with different visual means, under being on the other hand
One layer service provides the data of user mutual.
The present invention is the flow with reference to method according to embodiments of the present invention, equipment (system) and computer program product
Figure and/or block diagram are described.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram
Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided
The processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce
A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real
The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which is produced, to be included referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or
The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that in meter
Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, thus in computer or
The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in individual square frame or multiple square frames.
Although having been described for the alternative embodiment of the present invention, those skilled in the art once know basic creation
Property concept, then can make other change and modification to these embodiments.So, appended claims are intended to be construed to include can
Select embodiment and fall into having altered and changing for the scope of the invention.
Obviously, those skilled in the art can carry out various changes and modification without departing from this hair to the embodiment of the present invention
The spirit and scope of bright embodiment.So, if these modifications and variations of the embodiment of the present invention belong to the claims in the present invention
And its within the scope of equivalent technologies, then the present invention is also intended to comprising including these changes and modification.
Claims (10)
1. a kind of WLAN WLAN optimization methods, it is characterised in that methods described includes：
Receive the data of wlan network equipment collection；
Analysis model is set up by the intelligent algorithm of machine learning, the data analyzed using analysis model；
Network Optimization Strategy is determined according to the result of the analysis and execution is issued.
2. according to the method described in claim 1, it is characterised in that the data for receiving the collection of wlan network equipment, including：
The network equipment running state data, wireless environment data, user experience data of wlan network equipment collection are received, its
In, the data are wireless controller AC, wireless access point AP progress data acquisition and carry out squeeze operation transmission.
3. method according to claim 1 or 2, it is characterised in that the intelligent algorithm by machine learning, which is set up, divides
Model is analysed, the data are analyzed using analysis model, including：
By the intelligent algorithm of machine learning, set up wireless environment and perceive trend model, Consumer's Experience sensor model；
Based on the data, obtain whole net WLAN wireless environments coverage condition using wireless environment perception trend model analysis, do
Situation and network operation state trend are disturbed, wireless communication status is reduced, utilizes Consumer's Experience sensor model assay measures user's body
Situation is tested, and all Consumer's Experience situations of the wireless communication status and whole net are visualized.
4. method according to claim 3, it is characterised in that the determination Network Optimization Strategy simultaneously issues execution, including：
The Consumer's Experience situation obtained according to wireless WLAN environment and equipment running status and analysis, to the wireless network
State is diagnosed, analyze exist radio network problems, for the radio network problems determine Network Optimization Strategy and under
Hair is performed, wherein, the radio network problems include interference, access, the one or more of roaming.
5. according to the method described in claim 1, it is characterised in that methods described, in addition to：
Network Optimization Strategy is issued after execution, and obtaining wireless communication status by analysis model analysis feeds back, and with reference to net
Network optimisation strategy performs front and rear Consumer's Experience situation and wireless communication status difference, carries out the adjustment of Network Optimization Strategy, real
Existing closed loop convergence.
6. a kind of WLAN optimizes device, it is characterised in that including：Receiving unit, analytic unit, policy unit；Wherein,
Receiving unit, the data for receiving the collection of wlan network equipment；
The data, for setting up analysis model by the intelligent algorithm of machine learning, are entered by analytic unit using analysis model
Row analysis；
Policy unit, for determining Network Optimization Strategy according to the result of the analysis and issuing execution.
7. device according to claim 6, it is characterised in that the receiving unit, sets specifically for receiving wlan network
The network equipment running state data of standby collection, wireless environment data, user experience data, wherein, the data are wireless controlled
Device AC processed, wireless access point AP carry out data acquisition and carry out squeeze operation transmission.
8. the device according to claim 6 or 7, it is characterised in that the analytic unit, specifically for passing through machine learning
Intelligent algorithm, set up wireless environment perceive trend model, Consumer's Experience sensor model；Based on the data, wireless ring is utilized
Border perceives trend model analysis and obtains whole net WLAN wireless environments coverage condition, disturbed condition and network operation state trend, also
Former wireless communication status, using Consumer's Experience sensor model assay measures Consumer's Experience situation, and by the wireless communication status
Visualized with whole all Consumer's Experience situations of net.
9. device according to claim 8, it is characterised in that the policy unit, specifically for according to wireless WLAN rings
The Consumer's Experience situation that border and equipment running status and analysis are obtained, is diagnosed to the wireless communication status, analysis
The radio network problems of presence, determine Network Optimization Strategy for the radio network problems and issue execution, wherein, the nothing
Line network problem includes interference, access, the one or more of roaming.
10. device according to claim 6, it is characterised in that the analytic unit, is additionally operable under Network Optimization Strategy
Hair perform after, by the analysis model analysis obtain wireless communication status feed back, and with reference to Network Optimization Strategy perform before and after
Consumer's Experience situation and wireless communication status difference, carry out Network Optimization Strategy adjustment, realize closed loop restrain.
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| CN109274541A (en) * | 2018-11-19 | 2019-01-25 | 国家电网公司 | The method of adjustment and device of communication network |
| WO2021238277A1 (en) * | 2020-05-24 | 2021-12-02 | 中兴通讯股份有限公司 | Network optimisation method, server, network side device, system, and storage medium |
| WO2022105860A1 (en) * | 2020-11-23 | 2022-05-27 | 华为技术有限公司 | Method, system, and apparatus for terminal scanning, electronic device, and storage medium |
| CN117676638A (en) * | 2023-11-17 | 2024-03-08 | 上海市信息网络有限公司 | Wireless network optimization supervision system and method based on Internet of things |
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| CN102958082A (en) * | 2012-12-07 | 2013-03-06 | 广州杰赛科技股份有限公司 | Network optimization analysis method and system |
| US20140219156A1 (en) * | 2013-02-01 | 2014-08-07 | Thomson Licensing | Optimizing wireless local area network communications |
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| WO2021238277A1 (en) * | 2020-05-24 | 2021-12-02 | 中兴通讯股份有限公司 | Network optimisation method, server, network side device, system, and storage medium |
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