CN106506103A - A kind of multi-threshold frequency spectrum sensing method based on Noise Variance Estimation - Google Patents
A kind of multi-threshold frequency spectrum sensing method based on Noise Variance Estimation Download PDFInfo
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- CN106506103A CN106506103A CN201611033713.3A CN201611033713A CN106506103A CN 106506103 A CN106506103 A CN 106506103A CN 201611033713 A CN201611033713 A CN 201611033713A CN 106506103 A CN106506103 A CN 106506103A
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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
- H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
- H04B1/0003—Software-defined radio [SDR] systems, i.e. systems wherein components typically implemented in hardware, e.g. filters or modulators/demodulators, are implented using software, e.g. by involving an AD or DA conversion stage such that at least part of the signal processing is performed in the digital domain
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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
- H04B17/345—Interference values
Abstract
The present invention is claimed a kind of multi-threshold frequency spectrum sensing method based on Noise Variance Estimation, and the purpose of the method is to solve the problems, such as the energy measuring unstable properties under noise variance Uncertain environments.The invention uses the scheme of two steps perception, perceives and quick sensing including accurate.First, in the first step accurately perception cycle, noise power is estimated using the method for maximal possibility estimation；Secondly, in the second step quick sensing cycle, the noise power estimated with the first step adaptively sets multiple decision thresholds to cognitive user；Finally, cognitive user carries out energy measuring according to the multiple decision thresholds for setting, and obtains final court verdict.The invention can be in the case where detector be unknown to noise indeterminacy section, it is ensured that good detection performance, so as to overcome incorrect noise to detecting the impact of performance.
Description
Technical field
A kind of radio communication of the present invention and signal detection field, more particularly to one kind is estimated based on noise variance in cognition network
The multi-threshold frequency spectrum sensing method of meter.
Background technology
Cognitive radio (Cognitive Radio, CR) can improve frequency as a kind of dynamic frequency spectrum reutilization technology
Spectrum utilization rate, efficent use of resources, its develop the extensive concern for being subject to academia and industrial quarters.In cognition wireless network, recognize
User/time user (SU) is known first by whether there is primary user (PU) in active detecting mandate frequency spectrum, when in specific frequency range
When there is no primary user, cognitive device utilizes frequency spectrum cavity-pocket by reconfiguring its parameter.When PU occurs again, SU should
Timely vacate frequency spectrum to use to PU, to reduce the interference to PU.Therefore, frequency spectrum detection algorithm should have good reliability and
The rapidity of detection speed.Common frequency spectrum detection technology has：Matched filter detection, energy measuring, cyclostationary characteristic inspection
Survey, collaborative spectrum sensing and multiple antennas are detected.Wherein energy measuring is carried out simple and relatively low complexity and is widely used in frequently
During spectrum is perceived.But the selection of energy detector threshold is to rely on noise variance.In the actual environment, noise power be with
Time and position change within the specific limits.Little incorrect noise will cause to detect being remarkably decreased for performance.Therefore,
Energy measuring noise indeterminacy phenomenon, directly affects the robustness of detection performance.
The method of opposing incorrect noise has joint-detection, double threshold energy measuring, adaptive spectrum detection etc. at present.
But, the method for not carrying out energy measuring for estimating noise power.The method of most of energy measurings is all at the very start
Uncertain parameters given noise.And this method more can accurately estimate noise variance indeterminacy section, so as to adaptive
Answer ground dynamic that multi-threshold decision threshold is set, and there is preferable detection performance, particularly under complex environment, overcome noise
The uncertain impact to energy measuring threshold sets.
Content of the invention
Present invention seek to address that above problem of the prior art.Propose a kind of efficiently and accurately perception idle frequency spectrum
Multi-threshold frequency spectrum sensing method based on Noise Variance Estimation.
Technical scheme is as follows：
A kind of multi-threshold frequency spectrum sensing method based on Noise Variance Estimation, it include the step of accurately perceiving and quick sense
The step of knowing：In the accurate perception cycle, noise power is estimated using the method for maximal possibility estimation；In quick sensing
In cycle, multiple decision thresholds are adaptively set to cognitive user with the noise power for estimating；Finally, cognitive user root
Energy measuring is carried out according to the multiple decision thresholds for setting, final frequency spectrum perception result is obtained.
Further, the accurate perception stage is concretely comprised the following steps：
A1, the signal for receiving cognitive user carry out A/D conversion, obtain sampling samples value；
A2, sample value is sent into K × M bursters, obtain K groups, every group of M sample value；
A3, each group of sample value is individually carried out maximal possibility estimation seek its variance yields, obtain K estimate of variance；
A4, according to weak law of large number, obtain the interval estimated value of incorrect noise.
Further, quick sensing stage concretely comprises the following steps：
Error burst between B1, the estimated value for providing the uncertain interval of noise variance and actual value；
B2, according to error burst, take the uncertain interval upper boundary values of n noise variance and lower border value respectively, obtain
High-low threshold value to corresponding two groups of decision thresholds；
B3, the statistics that in this two groups of decision thresholds feeding quick sensing cycles, will be arrived with cognitive user (SU) quick sensing
Amount T is compared.
B4, finally by all court verdicts using majority criterions fusion obtain the final local court verdicts of SU.
Further, step A4 respectively obtains the estimated value of incorrect noise variance, estimates according to weak law of large number
The error amount existed between meter variance yields and realized variance value.Specifically include：Assume that K is very big but when tending not to infinity, obtain
Noise variance uncertainty estimation interval is：
Wherein,WithNoise variance uncertain interval estimation lower border value and upper boundary values are represented respectively,Table
Show the nominal variance of noise,Represent that the estimation difference of the uncertain interval coboundary of noise variance, ξ represent that noise variance is not true
The estimation difference of qualitative interval lower boundary,WithNoise variance uncertain interval actual lower border value and upper is represented respectively
Boundary value.
Further, in step B1, actual noise variance with the error band for estimating noise variance boundary value is：
Method of estimation wherein to ξ：
In the same manner：
Further, in step B2, n is 5, i.e., take respectively the uncertain interval upper boundary values of 5 noise variances and
Lower border value is：With
Further, the high-low threshold value of two groups of decision thresholds described in step B2 is；
Wherein, λH1、λH2、3、λH4、55 high decision thresholds being given, λ are represented respectivelyL1、λL2、3、λL4、5Represent respectively and be given
5 low decision thresholds, N represent signal of the cognitive user to receiving sample after sampling number, PfRepresent that false-alarm is general
Rate, Q-1Represent anti-normal Gaussian complementation integral function.
Advantages of the present invention and have the beneficial effect that：
The present invention is similar to IEEE802.22 grass to solve the energy measuring performance under noise variance Uncertain environments
Case, we use two step aware schemes, perceive and quick sensing including accurate.And estimate essence of the noise gate in the first step
Really the perception cycle is carried out.As noise power is to maintain constant in several minutes, therefore, make an uproar phase estimate is accurately perceived
Acoustical power can apply to the setting of quick sensing cycle thresholding.
The present invention has carried out an estimation, then according to estimation in the environment of incorrect noise to noise interval
Noise adaptively sets multiple judging thresholds and the signal that cognitive user is received is made decisions, and finally adopts majority
Criterion fusion obtains the final local court verdicts of SU, solves asking for incorrect noise in practical radio communication environment well
Topic, so that improve the accuracy of perception so that the utilization rate of frequency spectrum is obviously improved.
Under the wireless complex environment actual in combination of the invention, to making an uproar for occurring during the frequency spectrum perception of cognitive radio
Sound uncertainty has carried out an accurate estimation, and is setting multiple height decision thresholds to energy according to estimation interval value
Detection data carries out amalgamation judging so that this method can better adapt to actual complex wireless environments, and can be more preferable
Ground overcomes impact of the incorrect noise to whole perceptual performance.This method is more with practical value.
Description of the drawings
Fig. 1 is that present invention offer preferred embodiment is shown based on the flow process of the multi-threshold frequency spectrum sensing method of Noise Variance Estimation
It is intended to.
Specific embodiment
Accompanying drawing in below in conjunction with the embodiment of the present invention, to the embodiment of the present invention in technical scheme carry out clear, detailed
Carefully describe.Described embodiment is only a part of embodiment of the present invention.
As shown in Figure 1：We use two step aware schemes, perceive and quick sensing including accurate.And estimate noise
Thresholding was carried out in the accurate perception cycle of the first step.Due to noise power be to maintain in several minutes constant, therefore, accurate
The noise power for perceiving phase estimate can apply to the setting of quick sensing cycle thresholding.
Accurate perception stage is concretely comprised the following steps：
Step 1：The accurate perception cycle will receive signal y (t) and carry out A/D conversion, obtain sampling samples for Y1,Y2,...,
YK×M, corresponding sample value isSample value is sent into K × M bursters, K groups, every group of M sample value is obtained.Appoint
One group of sample value of anticipating is：yj1,yj2,...,yjM(j=1,2 ..., K).
Step 2：Jth (j=1,2 ..., K) group sample value is individually carried out maximal possibility estimation and seeks its variance yields
K can so be obtainedEstimated value
Step 3：According to weak law of large number,It is separate, obeysBe uniformly distributed,
There is mathematic expectaionThen for any ε>0 has：
Wherein
So obtaining having when K tends to infinite：
Known by formula (7)：
Can be calculated in conjunction with formula (3) and formula (4)WithAs follows：
But K can not possibly take infinity in practice.Because K is bigger, complexity is higher, and detection time is longer, leaves SU for
The time of transmission is less.For this purpose, assuming that K is very big but when tending not to infinity, obtaining noise variance uncertainty estimation interval
For：
Quick sensing stage concretely comprises the following steps：
Step one：Due to limited sampled value, the noise variance interval for causing the noise variance that estimates interval with actual is deposited
In an error.So actual noise variance with the error band for estimating noise variance boundary value is：
Method of estimation wherein to ξ：
In the same manner：
Step 2：We can take the uncertain interval upper boundary values of 5 noise variances respectively and lower border value is：WithSo as to obtain two groups of decision thresholds, respectively：
Step 3：This two groups of decision thresholds were sent in quick sensing cycles, with SU quick sensings to statistic T carry out
Relatively, all court verdicts are obtained the final local court verdicts of SU using the fusion of majority criterions finally.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limits the scope of the invention.?
After the content of the record for having read the present invention, technical staff can be made various changes or modifications to the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (7)
1. a kind of multi-threshold frequency spectrum sensing method based on Noise Variance Estimation, it is characterised in that the step of including accurate perception
And the step of quick sensing：In the accurate perception cycle, noise power is estimated using the method for maximal possibility estimation；?
In the quick sensing cycle, multiple decision thresholds are adaptively set to cognitive user with the noise power for estimating；Finally, recognize
Know that user carries out energy measuring according to the multiple decision thresholds for setting, obtain final frequency spectrum perception result, i.e., frequency spectrum idle or
Occupy.
2. the multi-threshold frequency spectrum sensing method based on Noise Variance Estimation according to claim 1, it is characterised in that described
Accurate perception stage is concretely comprised the following steps：
A1, the signal for receiving cognitive user carry out A/D conversion, obtain sampling samples value；
A2, sample value is sent into K × M bursters, obtain K groups, every group of M sample value；
A3, each group of sample value is individually carried out maximal possibility estimation seek its variance yields, obtain K estimate of variance；
A4, according to weak law of large number, obtain the interval estimated value of incorrect noise.
3. the multi-threshold frequency spectrum sensing method based on Noise Variance Estimation according to claim 1, it is characterised in that quick
Perception stage is concretely comprised the following steps：
Error burst between B1, the estimated value for providing the uncertain interval of noise variance and actual value；
B2, according to error burst, take the uncertain interval upper boundary values of n noise variance and lower border value respectively, it is right to obtain
The high-low threshold value of the two groups of decision thresholds that answers；
B3, this two groups of decision thresholds were sent in quick sensing cycles, with cognitive user SU quick sensing to statistic T carry out
Relatively.
B4, finally by all court verdicts using majority criterions fusion obtain the final local court verdicts of SU.
4. the multi-threshold frequency spectrum sensing method based on Noise Variance Estimation according to claim 2, it is characterised in that described
Step A4 respectively obtains estimated value, estimate variance value and the realized variance value of incorrect noise variance according to weak law of large number
Between exist error amount, specifically include：Assume that K is very big but when tending not to infinity, obtain noise variance uncertainty estimation
Interval is：
Wherein,WithNoise variance uncertain interval estimation lower border value and upper boundary values are represented respectively,Expression is made an uproar
The nominal variance of sound, θ represent that the estimation difference of the uncertain interval coboundary of noise variance, ξ represent that noise variance is uncertain
The estimation difference of interval lower boundary,WithNoise variance uncertain interval actual lower border value and coboundary are represented respectively
Value.
5. the multi-threshold frequency spectrum sensing method based on Noise Variance Estimation according to claim 3, it is characterised in that described
In step B1, actual noise variance with the error band for estimating noise variance boundary value is：
Method of estimation wherein to ξ：
In the same manner：
6. the multi-threshold frequency spectrum sensing method based on Noise Variance Estimation according to claim 3, it is characterised in that described
In step B2, n is 5, i.e., take the uncertain interval upper boundary values of 5 noise variances respectively and lower border value is：With
7. the multi-threshold frequency spectrum sensing method based on Noise Variance Estimation according to claim 3, it is characterised in that described
The high-low threshold value of two groups of decision thresholds described in step B2 is；
Wherein, λH1、λH2、3、λH4、55 high decision thresholds being given, λ are represented respectivelyL1、λL2、3、λL4、5Be given 5 are represented respectively
Low decision threshold, N represent signal of the cognitive user to receiving sample after sampling number, PfRepresent false-alarm probability, Q-1
Represent anti-normal Gaussian complementation integral function.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105119668A (en) * | 2015-07-22 | 2015-12-02 | 南京邮电大学 | Iterative spectrum sensing method based on double judgment |
| US20160197748A1 (en) * | 2013-05-27 | 2016-07-07 | Southeast University | Blind spectrum sensing method and device based on fast fourier transform |
| CN105813089A (en) * | 2016-05-05 | 2016-07-27 | 宁波大学 | Matched filtering spectrum sensing method against noise indeterminacy |
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2016
- 2016-11-22 CN CN201611033713.3A patent/CN106506103A/en not_active Withdrawn
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160197748A1 (en) * | 2013-05-27 | 2016-07-07 | Southeast University | Blind spectrum sensing method and device based on fast fourier transform |
| CN105119668A (en) * | 2015-07-22 | 2015-12-02 | 南京邮电大学 | Iterative spectrum sensing method based on double judgment |
| CN105813089A (en) * | 2016-05-05 | 2016-07-27 | 宁波大学 | Matched filtering spectrum sensing method against noise indeterminacy |
Non-Patent Citations (1)
| Title |
|---|
| XIAOFENG XU: ""An Algorithm for Energy Detection Based on Noise Variance Estimation under Noise Uncertainy"", 《2012 IEEE 14TH INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY》 * |
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