CN106100776B - Frequency spectrum sensing method based on wireless station Grid Monitoring System - Google Patents
Frequency spectrum sensing method based on wireless station Grid Monitoring System Download PDFInfo
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- CN106100776B CN106100776B CN201610762960.0A CN201610762960A CN106100776B CN 106100776 B CN106100776 B CN 106100776B CN 201610762960 A CN201610762960 A CN 201610762960A CN 106100776 B CN106100776 B CN 106100776B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
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Abstract
The invention discloses a kind of frequency spectrum sensing methods based on wireless station Grid Monitoring System, it is the following steps are included: carry out spectral characteristic mark according to data of the local less radio-frequency environment to local detection result using monitoring station as single node；Then the frequency data by single node perception pass through transmission channel to gridding control centre；Centralized collaborative perception is carried out to single-node data using gridding control centre as data fusion node, and makes comprehensive judgement.The present invention is perceived in monitoring station using single node, and local sensing results are sent to gridding control centre and uniformly carry out the warm processing of data by each sensing node.Reach the detection threshold of system requirements by the cooperation between detection node, to reduce the burden of requirement and single detection node of the monitoring system to single detection node, effectively eliminates the influence of shadow effect.
Description
Technical field
The present invention relates to wireless station monitoring technical field, specifically a kind of frequency based on wireless station Grid Monitoring System
Compose cognitive method.
Background technique
Frequency spectrum perception technology is that the basis of gridding monitoring application and premise, existing frequency spectrum perception technology can be divided into list
Node perceived and coordination perception, wherein single node perception refers to that individual node carries out frequency spectrum spy according to local less radio-frequency environment
Property mark；And collaborative perception is then that sensing results by data fusion, based on multiple nodes will be after data carry out relevant treatment
Comprehensive judgement.Single node cognition technology includes matched filter detection, energy measuring, cyclostationary characteristic detection and covariance
Matrix detects 4 kinds, wherein energy detection algorithm, and cardinal principle is measured in certain section of observation time and received in special frequency channel
Then the gross energy of signal whether there is compared with a certain setting thresholding to adjudicate main signal.Since the algorithm complexity is lower,
Implement simply, while not needing any prior information, is most general perception algorithm.And matched filter detection algorithm, be
Know the optimum detection algorithm in the case of primary user's signal prior information (such as modulation type, shaping pulse, frame format).The algorithm
Advantage be detection signal-to-noise ratio can be made to maximize, same performance restriction under it is few compared with number of sampling points needed for energy measuring,
Therefore the processing time is shorter.Cyclostationary characteristic detection algorithm, principle are by analysis Cyclic Autocorrelation Function or two dimension
The method of frequency spectrum correlation function obtains signal spectrum ASSOCIATE STATISTICS characteristic, distinguishes main signal using the periodicity that it is presented and makes an uproar
Sound.The algorithm still has good detection performance under very low signal-to-noise ratio, and is directed to the unique statistics of various signal types
Feature carries out cyclic-spectral Analysis, can overcome malicious interference signal, greatly improve the performance and efficiency of detection.Covariance matrix inspection
Method of determining and calculating establishes sample of signal covariance matrix, and maximum, the minimal eigenvalue ratio with calculating matrix using the correlation of main signal
The method of rate makes judgement.
Frequency spectrum perception can accurately detect that signal-to-noise ratio (SNR) is greater than the authorization user signal of a certain threshold value, usually
The threshold value of this SNR be it is very low, for single node perception for, to reach this requirement and be not easy to.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of based on wireless station Grid Monitoring System
Frequency spectrum sensing method.
The purpose of the present invention is achieved through the following technical solutions: the frequency spectrum based on wireless station Grid Monitoring System
Cognitive method, it the following steps are included:
S1: frequency is carried out according to data of the local less radio-frequency environment to local detection result using monitoring station as single node
Spectral property mark；
S2: the frequency data of single node perception pass through transmission channel to gridding control centre；
S3: gridding control centre carries out centralized collaborative perception to single-node data as data fusion node, and does
Comprehensive judgement out.
In the step S1, local collaborative perception is carried out to mobile monitoring station, then with Cooperative data fusion point work
Spectral characteristic mark is carried out for new single node.
In the step S1, a sensitivity is preset for resisting the shadow of multipath fading generation to all single nodes
It rings.
In the step S1, the data of local detection result are compressed, reduce data transfer overhead.
The step S3, decompresses the single-node data for being transferred to gridding control centre, and to decompression after
Data carry out collaborative perception, and specific collaborative perception includes following sub-step::
S301: setting threshold value, all single-node datas of scan round and the single node signal for identifying different signal-to-noise ratio；
S302: whether identification burst signal-to-noise ratio is greater than threshold value；
S303: if id signal signal-to-noise ratio is greater than threshold value, the single node that signal-to-noise ratio is in similar level is sorted out, so
After carry out unified collaborative perception, extract frequency data；Otherwise, single-node data is continued to scan on；
S304: different synergistic results are notified other nodes by gridding control centre, are declared channel occupancy situation, are avoided sending out
Raw channel disturbance or competition.
In the step S3, it includes to the judgement of single node fused data and list that gridding control centre, which carries out comprehensive judgement,
The judgement of channel transmission data between node.
The monitoring station includes fixed monitoring station, mobile monitoring station and central monitoring station.
The beneficial effects of the present invention are: the present invention, using centralized collaborative perception, each sensing node ties local perception
Fruit is sent to gridding control centre and uniformly carries out data fusion, makes a policy.Reach system by the cooperation between detection node
It is required that detection threshold, to reduce the burden of requirement and single detection node of the monitoring system to single detection node, effectively
Ground eliminates the influence of shadow effect.
Detailed description of the invention
Fig. 1 is the method for the present invention step schematic diagram；
Fig. 2 is the centralized collaborative perception flow chart of the present invention；
Fig. 3 is monitoring system structure diagram of the present invention.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawing, but protection scope of the present invention is not limited to
It is as described below.
Based on the frequency spectrum sensing method of wireless station Grid Monitoring System, it the following steps are included:
S1: frequency is carried out according to data of the local less radio-frequency environment to local detection result using monitoring station as single node
Spectral property mark；
S2: the frequency data of single node perception pass through transmission channel to gridding control centre；
S3: gridding control centre carries out centralized collaborative perception to single-node data as data fusion node, and does
Comprehensive judgement out.
In the step S1, local collaborative perception is carried out to mobile monitoring station, then with Cooperative data fusion point work
Spectral characteristic mark is carried out for new single node.
In the step S1, a sensitivity is preset for resisting the shadow of multipath fading generation to all single nodes
It rings.
In the step S1, the data of local detection result are compressed, reduce data transfer overhead.
The step S3, decompresses the single-node data for being transferred to gridding control centre, and to decompression after
Data carry out collaborative perception, and specific collaborative perception includes following sub-step::
S301: setting threshold value, all single-node datas of scan round and the single node signal for identifying different signal-to-noise ratio；
S302: whether identification burst signal-to-noise ratio is greater than threshold value；
S303: if id signal signal-to-noise ratio is greater than threshold value, the single node that signal-to-noise ratio is in similar level is sorted out, so
After carry out unified collaborative perception, extract frequency data；Otherwise, single-node data is continued to scan on；
S304: different synergistic results are notified other nodes by gridding control centre, are declared channel occupancy situation, are avoided sending out
Raw channel disturbance or competition.
In the step S3, it includes to the judgement of single node fused data and list that gridding control centre, which carries out comprehensive judgement,
The judgement of channel transmission data between node.
The monitoring station includes fixed monitoring station, mobile monitoring station and central monitoring station.
As shown in figure 3, being wireless station Grid Monitoring System structural schematic diagram of the present invention, multiple monitoring stations acquire data,
It is transferred to gridding control centre.The frequency spectrum sensing method based on wireless station Grid Monitoring System, such as Fig. 1, Fig. 2 institute
Show, using monitoring station as single node perceived frequency signal, and spectral characteristic mark is carried out to frequency signal, while monitoring station is arranged
One signal sensitivity, for resisting influence caused by multipath fading, then the data of acquisition are suitably compressed in monitoring station
After transmit, reduce transport overhead.In gridding control centre, all single nodes constituted to monitoring station in monitoring network collect
Chinese style collaborative perception, while the data of each single node transmission are handled, and processing result is notified to other nodes in time, statement letter
Road occupancy situation, avoids channel competition and interference.Gridding control centre is based on comprehensive court verdict, makes a policy, and output is dry
Disturb signal message and illegal station signal message.
Claims (7)
1. the frequency spectrum sensing method based on wireless station Grid Monitoring System, which is characterized in that it the following steps are included:
S1: it is special that frequency spectrum is carried out according to data of the local less radio-frequency environment to local detection result using monitoring station as single node
Property mark；
S2: the frequency data of single node perception pass through transmission channel to gridding control centre；
S3: gridding control centre carries out centralized collaborative perception to single-node data as data fusion node, and makes comprehensive
Judgement is closed, specific collaborative perception includes following sub-step:
S301: setting threshold value, all single-node datas of scan round and the single node signal for identifying different signal-to-noise ratio；
S302: whether identification burst signal-to-noise ratio is greater than threshold value；
S303: if id signal signal-to-noise ratio be greater than threshold value, by signal-to-noise ratio be in similar level single node classification, then into
The unified collaborative perception of row, extracts frequency data；Otherwise, single-node data is continued to scan on；
S304: different synergistic results are notified other nodes by gridding control centre, are declared channel occupancy situation, are avoided believing
Road interference or competition.
2. the frequency spectrum sensing method as described in claim 1 based on wireless station Grid Monitoring System, it is characterised in that: described
Step S1 in, local collaborative perception is carried out to mobile monitoring station, then using Cooperative data fusion point as new single node
Carry out spectral characteristic mark.
3. the frequency spectrum sensing method as described in claim 1 based on wireless station Grid Monitoring System, it is characterised in that: described
Step S1 in, to all single nodes preset a sensitivity for resist multipath fading generation influence.
4. the frequency spectrum sensing method as described in claim 1 based on wireless station Grid Monitoring System, it is characterised in that: described
Step S1 in, the data of local detection result are compressed, reduce data transfer overhead.
5. the frequency spectrum sensing method as claimed in claim 4 based on wireless station Grid Monitoring System, it is characterised in that: described
Step S3, the single-node data for being transferred to gridding control centre is decompressed, and the data after decompression are cooperateed with
Perception.
6. the frequency spectrum sensing method as described in claim 1 based on wireless station Grid Monitoring System, it is characterised in that: described
Step S3 in, it includes to the letter between the judgement of single node fused data and single node that gridding control centre, which carries out comprehensive judgement,
The judgement of road transmission data.
7. the frequency spectrum sensing method as described in claim 1 based on wireless station Grid Monitoring System, it is characterised in that: described
Monitoring station include fixed monitoring station, mobile monitoring station and central monitoring station.
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| CN108732423A (en) * | 2018-03-06 | 2018-11-02 | 西安大衡天成信息科技有限公司 | A kind of spectrum monitoring data processing system and method |
| WO2019170001A1 (en) * | 2018-03-06 | 2019-09-12 | 西安大衡天成信息科技有限公司 | Frequency spectrum monitoring data structured representation method, and data processing method and compression method |
| CN108809450B (en) * | 2018-08-01 | 2021-02-26 | 中国科学院上海微系统与信息技术研究所 | Distributed spectrum monitoring method |
| CN114205821B (en) * | 2021-11-30 | 2023-08-08 | 广州万城万充新能源科技有限公司 | Wireless radio frequency anomaly detection method based on depth prediction coding neural network |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101437295A (en) * | 2008-12-09 | 2009-05-20 | 重庆邮电大学 | Method for detecting perception radio collaboration frequency spectrum based on SNR compare |
| WO2013127343A1 (en) * | 2012-02-27 | 2013-09-06 | 联发科技（新加坡）私人有限公司 | Method and apparatus for using cognitive radio technology |
| CN103338458A (en) * | 2013-07-11 | 2013-10-02 | 东南大学 | Cooperative spectrum sensing method used for cognitive radio system |
| CN103888203A (en) * | 2014-03-05 | 2014-06-25 | 南京邮电大学 | Method for cooperative spectrum sensing optimization based on signal to noise ratio screening |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104022839B (en) * | 2014-06-23 | 2016-04-20 | 哈尔滨工业大学 | A kind of information fusion decision method being applied to cooperative spectrum sensing |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101437295A (en) * | 2008-12-09 | 2009-05-20 | 重庆邮电大学 | Method for detecting perception radio collaboration frequency spectrum based on SNR compare |
| WO2013127343A1 (en) * | 2012-02-27 | 2013-09-06 | 联发科技（新加坡）私人有限公司 | Method and apparatus for using cognitive radio technology |
| CN103338458A (en) * | 2013-07-11 | 2013-10-02 | 东南大学 | Cooperative spectrum sensing method used for cognitive radio system |
| CN103888203A (en) * | 2014-03-05 | 2014-06-25 | 南京邮电大学 | Method for cooperative spectrum sensing optimization based on signal to noise ratio screening |
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